Selection

Annotation:

StepAnnotation
Step 1: Input dataset
select at runtime
Step 2: Input dataset
select at runtime
Step 3: Input dataset
select at runtime
Step 4: Input dataset
select at runtime
Step 5: Input dataset
select at runtime
Step 6: Input dataset
select at runtime
Step 7: Input dataset
select at runtime
Step 8: Input dataset
select at runtime
Step 9: Input dataset
select at runtime
Step 10: Input dataset
select at runtime
Step 11: Input dataset
select at runtime
Step 12: Input dataset
select at runtime
Step 13: Input dataset
select at runtime
Step 14: Input dataset
select at runtime
Step 15: Input dataset
select at runtime
Step 16: Input dataset
select at runtime
Step 17: Input dataset
select at runtime
Step 18: Input dataset
select at runtime
Step 19: Input dataset
select at runtime
Step 20: Input dataset
select at runtime
Step 21: Input dataset
select at runtime
Step 22: Input dataset
select at runtime
Step 23: Input dataset
select at runtime
Step 24: Input dataset
select at runtime
Step 25: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: methyltransferase
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 26: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: RNA-dependent RNA polymerase
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 27: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: ORF8
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 28: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: ORF7a
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 29: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: ORF6
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 30: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: ORF3a
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 31: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: Nucleoprotein
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 32: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: Membrane
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 33: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: Envelope
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 34: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: Spike
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 35: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: endornase
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 36: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: exonuclease
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 37: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: helicase
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 38: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: nsp10
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 39: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: nsp9
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 40: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: nsp8
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 41: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: nsp7
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 42: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: nsp6
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 43: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: 3C
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 44: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: nsp4
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 45: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: nsp3
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 46: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: nsp2
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 47: Align sequences
Output dataset 'output' from step 1
Select preset
SARS-CoV-2: leader
True
Use a predefined background
None
Advanced options:
Not available.
Codon
Blocks substitution
False
False
False
Step 48: Align sequences
Output dataset 'output' from step 2
Select preset
SARS-CoV-2: RNA-dependent RNA polymerase
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 49: Align sequences
Output dataset 'output' from step 3
Select preset
SARS-CoV-2: methyltransferase
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 50: Align sequences
Output dataset 'output' from step 4
Select preset
SARS-CoV-2: ORF8
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 51: Align sequences
Output dataset 'output' from step 5
Select preset
SARS-CoV-2: ORF7a
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 52: Align sequences
Output dataset 'output' from step 6
Select preset
SARS-CoV-2: ORF6
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 53: Align sequences
Output dataset 'output' from step 7
Select preset
SARS-CoV-2: ORF3a
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 54: Align sequences
Output dataset 'output' from step 8
Select preset
SARS-CoV-2: Nucleoprotein
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 55: Align sequences
Output dataset 'output' from step 9
Select preset
SARS-CoV-2: Membrane
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 56: Align sequences
Output dataset 'output' from step 10
Select preset
SARS-CoV-2: Envelope
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 57: Align sequences
Output dataset 'output' from step 11
Select preset
SARS-CoV-2: Spike
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 58: Align sequences
Output dataset 'output' from step 12
Select preset
SARS-CoV-2: endornase
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 59: Align sequences
Output dataset 'output' from step 13
Select preset
SARS-CoV-2: exonuclease
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 60: Align sequences
Output dataset 'output' from step 14
Select preset
SARS-CoV-2: helicase
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 61: Align sequences
Output dataset 'output' from step 15
Select preset
SARS-CoV-2: nsp10
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 62: Align sequences
Output dataset 'output' from step 16
Select preset
SARS-CoV-2: nsp9
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 63: Align sequences
Output dataset 'output' from step 17
Select preset
SARS-CoV-2: nsp8
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 64: Align sequences
Output dataset 'output' from step 18
Select preset
SARS-CoV-2: nsp7
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 65: Align sequences
Output dataset 'output' from step 19
Select preset
SARS-CoV-2: nsp6
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 66: Align sequences
Output dataset 'output' from step 20
Select preset
SARS-CoV-2: 3C
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 67: Align sequences
Output dataset 'output' from step 21
Select preset
SARS-CoV-2: nsp4
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 68: Align sequences
Output dataset 'output' from step 22
Select preset
SARS-CoV-2: nsp3
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 69: Align sequences
Output dataset 'output' from step 23
Select preset
SARS-CoV-2: nsp2
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 70: Align sequences
Output dataset 'output' from step 24
Select preset
SARS-CoV-2: leader
Advanced options:
Not available.
Codon
HIV between+F
False
True
True
Step 71: Convert BAM
Output dataset 'output' from step 25
0
0
Step 72: Convert BAM
Output dataset 'output' from step 26
0
0
Step 73: Convert BAM
Output dataset 'output' from step 27
0
0
Step 74: Convert BAM
Output dataset 'output' from step 28
0
0
Step 75: Convert BAM
Output dataset 'output' from step 29
0
0
Step 76: Convert BAM
Output dataset 'output' from step 30
0
0
Step 77: Convert BAM
Output dataset 'output' from step 31
0
0
Step 78: Convert BAM
Output dataset 'output' from step 32
0
0
Step 79: Convert BAM
Output dataset 'output' from step 33
0
0
Step 80: Convert BAM
Output dataset 'output' from step 34
0
0
Step 81: Convert BAM
Output dataset 'output' from step 35
0
0
Step 82: Convert BAM
Output dataset 'output' from step 36
0
0
Step 83: Convert BAM
Output dataset 'output' from step 37
0
0
Step 84: Convert BAM
Output dataset 'output' from step 38
0
0
Step 85: Convert BAM
Output dataset 'output' from step 39
0
0
Step 86: Convert BAM
Output dataset 'output' from step 40
0
0
Step 87: Convert BAM
Output dataset 'output' from step 41
0
0
Step 88: Convert BAM
Output dataset 'output' from step 42
0
0
Step 89: Convert BAM
Output dataset 'output' from step 43
0
0
Step 90: Convert BAM
Output dataset 'output' from step 44
0
0
Step 91: Convert BAM
Output dataset 'output' from step 45
0
0
Step 92: Convert BAM
Output dataset 'output' from step 46
0
0
Step 93: Convert BAM
Output dataset 'output' from step 47
0
0
Step 94: Convert BAM
Output dataset 'output' from step 48
0
0
Step 95: Convert BAM
Output dataset 'output' from step 49
0
0
Step 96: Convert BAM
Output dataset 'output' from step 50
0
0
Step 97: Convert BAM
Output dataset 'output' from step 51
0
0
Step 98: Convert BAM
Output dataset 'output' from step 52
0
0
Step 99: Convert BAM
Output dataset 'output' from step 53
0
0
Step 100: Convert BAM
Output dataset 'output' from step 54
0
0
Step 101: Convert BAM
Output dataset 'output' from step 55
0
0
Step 102: Convert BAM
Output dataset 'output' from step 56
0
0
Step 103: Convert BAM
Output dataset 'output' from step 57
0
0
Step 104: Convert BAM
Output dataset 'output' from step 58
0
0
Step 105: Convert BAM
Output dataset 'output' from step 59
0
0
Step 106: Convert BAM
Output dataset 'output' from step 60
0
0
Step 107: Convert BAM
Output dataset 'output' from step 61
0
0
Step 108: Convert BAM
Output dataset 'output' from step 62
0
0
Step 109: Convert BAM
Output dataset 'output' from step 63
0
0
Step 110: Convert BAM
Output dataset 'output' from step 64
0
0
Step 111: Convert BAM
Output dataset 'output' from step 65
0
0
Step 112: Convert BAM
Output dataset 'output' from step 66
0
0
Step 113: Convert BAM
Output dataset 'output' from step 67
0
0
Step 114: Convert BAM
Output dataset 'output' from step 68
0
0
Step 115: Convert BAM
Output dataset 'output' from step 69
0
0
Step 116: Convert BAM
Output dataset 'output' from step 70
0
0
Step 117: Replace ambiguous codons
Output dataset 'output' from step 71
Step 118: Replace ambiguous codons
Output dataset 'output' from step 72
Step 119: Replace ambiguous codons
Output dataset 'output' from step 73
Step 120: Replace ambiguous codons
Output dataset 'output' from step 74
Step 121: Replace ambiguous codons
Output dataset 'output' from step 75
Step 122: Replace ambiguous codons
Output dataset 'output' from step 76
Step 123: Replace ambiguous codons
Output dataset 'output' from step 77
Step 124: Replace ambiguous codons
Output dataset 'output' from step 78
Step 125: Replace ambiguous codons
Output dataset 'output' from step 79
Step 126: Replace ambiguous codons
Output dataset 'output' from step 80
Step 127: Replace ambiguous codons
Output dataset 'output' from step 81
Step 128: Replace ambiguous codons
Output dataset 'output' from step 82
Step 129: Replace ambiguous codons
Output dataset 'output' from step 83
Step 130: Replace ambiguous codons
Output dataset 'output' from step 84
Step 131: Replace ambiguous codons
Output dataset 'output' from step 85
Step 132: Replace ambiguous codons
Output dataset 'output' from step 86
Step 133: Replace ambiguous codons
Output dataset 'output' from step 87
Step 134: Replace ambiguous codons
Output dataset 'output' from step 88
Step 135: Replace ambiguous codons
Output dataset 'output' from step 89
Step 136: Replace ambiguous codons
Output dataset 'output' from step 90
Step 137: Replace ambiguous codons
Output dataset 'output' from step 91
Step 138: Replace ambiguous codons
Output dataset 'output' from step 92
Step 139: Replace ambiguous codons
Output dataset 'output' from step 93
Step 140: Replace ambiguous codons
Output dataset 'output' from step 94
Step 141: Replace ambiguous codons
Output dataset 'output' from step 95
Step 142: Replace ambiguous codons
Output dataset 'output' from step 96
Step 143: Replace ambiguous codons
Output dataset 'output' from step 97
Step 144: Replace ambiguous codons
Output dataset 'output' from step 98
Step 145: Replace ambiguous codons
Output dataset 'output' from step 99
Step 146: Replace ambiguous codons
Output dataset 'output' from step 100
Step 147: Replace ambiguous codons
Output dataset 'output' from step 101
Step 148: Replace ambiguous codons
Output dataset 'output' from step 102
Step 149: Replace ambiguous codons
Output dataset 'output' from step 103
Step 150: Replace ambiguous codons
Output dataset 'output' from step 104
Step 151: Replace ambiguous codons
Output dataset 'output' from step 105
Step 152: Replace ambiguous codons
Output dataset 'output' from step 106
Step 153: Replace ambiguous codons
Output dataset 'output' from step 107
Step 154: Replace ambiguous codons
Output dataset 'output' from step 108
Step 155: Replace ambiguous codons
Output dataset 'output' from step 109
Step 156: Replace ambiguous codons
Output dataset 'output' from step 110
Step 157: Replace ambiguous codons
Output dataset 'output' from step 111
Step 158: Replace ambiguous codons
Output dataset 'output' from step 112
Step 159: Replace ambiguous codons
Output dataset 'output' from step 113
Step 160: Replace ambiguous codons
Output dataset 'output' from step 114
Step 161: Replace ambiguous codons
Output dataset 'output' from step 115
Step 162: Replace ambiguous codons
Output dataset 'output' from step 116
Step 163: TN93 Cluster
Output dataset 'output' from step 117
Output dataset 'saved_reference' from step 25
True
200
0.0005
resolve
All
100
1.0
Step 164: TN93 Cluster
Output dataset 'output' from step 118
Output dataset 'saved_reference' from step 26
True
200
0.0005
resolve
All
100
1.0
Step 165: TN93 Cluster
Output dataset 'output' from step 119
Output dataset 'saved_reference' from step 27
True
200
0.0005
resolve
All
100
1.0
Step 166: TN93 Cluster
Output dataset 'output' from step 120
Output dataset 'saved_reference' from step 28
True
200
0.0005
resolve
All
100
1.0
Step 167: TN93 Cluster
Output dataset 'output' from step 121
Output dataset 'saved_reference' from step 29
True
200
0.0005
resolve
All
100
1.0
Step 168: TN93 Cluster
Output dataset 'output' from step 122
Output dataset 'saved_reference' from step 30
True
200
0.0005
resolve
All
100
1.0
Step 169: TN93 Cluster
Output dataset 'output' from step 123
Output dataset 'saved_reference' from step 31
True
200
0.0005
resolve
All
100
1.0
Step 170: TN93 Cluster
Output dataset 'output' from step 124
Output dataset 'saved_reference' from step 32
True
200
0.0005
resolve
All
100
1.0
Step 171: TN93 Cluster
Output dataset 'output' from step 125
Output dataset 'saved_reference' from step 33
True
200
0.0005
resolve
All
100
1.0
Step 172: TN93 Cluster
Output dataset 'output' from step 126
Output dataset 'saved_reference' from step 34
True
200
0.0005
resolve
All
100
1.0
Step 173: TN93 Cluster
Output dataset 'output' from step 127
Output dataset 'saved_reference' from step 35
True
200
0.0005
resolve
All
100
1.0
Step 174: TN93 Cluster
Output dataset 'output' from step 128
Output dataset 'saved_reference' from step 36
True
200
0.0005
resolve
All
100
1.0
Step 175: TN93 Cluster
Output dataset 'output' from step 129
Output dataset 'saved_reference' from step 37
True
200
0.0005
resolve
All
100
1.0
Step 176: TN93 Cluster
Output dataset 'output' from step 130
Output dataset 'saved_reference' from step 38
True
200
0.0005
resolve
All
100
1.0
Step 177: TN93 Cluster
Output dataset 'output' from step 131
Output dataset 'saved_reference' from step 39
True
200
0.0005
resolve
All
100
1.0
Step 178: TN93 Cluster
Output dataset 'output' from step 132
Output dataset 'saved_reference' from step 40
True
200
0.0005
resolve
All
100
1.0
Step 179: TN93 Cluster
Output dataset 'output' from step 133
Output dataset 'saved_reference' from step 41
True
200
0.0005
resolve
All
100
1.0
Step 180: TN93 Cluster
Output dataset 'output' from step 134
Output dataset 'saved_reference' from step 42
True
200
0.0005
resolve
All
100
1.0
Step 181: TN93 Cluster
Output dataset 'output' from step 135
Output dataset 'saved_reference' from step 43
True
200
0.0005
resolve
All
100
1.0
Step 182: TN93 Cluster
Output dataset 'output' from step 136
Output dataset 'saved_reference' from step 44
True
200
0.0005
resolve
All
100
1.0
Step 183: TN93 Cluster
Output dataset 'output' from step 137
Output dataset 'saved_reference' from step 45
True
200
0.0005
resolve
All
100
1.0
Step 184: TN93 Cluster
Output dataset 'output' from step 138
Output dataset 'saved_reference' from step 46
True
200
0.0005
resolve
All
100
1.0
Step 185: TN93 Cluster
Output dataset 'output' from step 139
Output dataset 'saved_reference' from step 47
True
200
0.0005
resolve
All
100
1.0
Step 186: TN93 Cluster
Output dataset 'output' from step 140
Output dataset 'saved_reference' from step 26
True
200
0.0005
resolve
All
100
1.0
Step 187: TN93 Cluster
Output dataset 'output' from step 141
Output dataset 'saved_reference' from step 25
True
200
0.0005
resolve
All
100
1.0
Step 188: TN93 Cluster
Output dataset 'output' from step 142
Output dataset 'saved_reference' from step 27
True
200
0.0005
resolve
All
100
1.0
Step 189: TN93 Cluster
Output dataset 'output' from step 143
Output dataset 'saved_reference' from step 28
True
200
0.0005
resolve
All
100
1.0
Step 190: TN93 Cluster
Output dataset 'output' from step 144
Output dataset 'saved_reference' from step 29
True
200
0.0005
resolve
All
100
1.0
Step 191: TN93 Cluster
Output dataset 'output' from step 145
Output dataset 'saved_reference' from step 30
True
200
0.0005
resolve
All
100
1.0
Step 192: TN93 Cluster
Output dataset 'output' from step 146
Output dataset 'saved_reference' from step 31
True
200
0.0005
resolve
All
100
1.0
Step 193: TN93 Cluster
Output dataset 'output' from step 147
Output dataset 'saved_reference' from step 32
True
200
0.0005
resolve
All
100
1.0
Step 194: TN93 Cluster
Output dataset 'output' from step 148
Output dataset 'saved_reference' from step 33
True
200
0.0005
resolve
All
100
1.0
Step 195: TN93 Cluster
Output dataset 'output' from step 149
Output dataset 'saved_reference' from step 34
True
200
0.0005
resolve
All
100
1.0
Step 196: TN93 Cluster
Output dataset 'output' from step 150
Output dataset 'saved_reference' from step 35
True
200
0.0005
resolve
All
100
1.0
Step 197: TN93 Cluster
Output dataset 'output' from step 151
Output dataset 'saved_reference' from step 36
True
200
0.0005
resolve
All
100
1.0
Step 198: TN93 Cluster
Output dataset 'output' from step 152
Output dataset 'saved_reference' from step 37
True
200
0.0005
resolve
All
100
1.0
Step 199: TN93 Cluster
Output dataset 'output' from step 153
Output dataset 'saved_reference' from step 38
True
200
0.0005
resolve
All
100
1.0
Step 200: TN93 Cluster
Output dataset 'output' from step 154
Output dataset 'saved_reference' from step 39
True
200
0.0005
resolve
All
100
1.0
Step 201: TN93 Cluster
Output dataset 'output' from step 155
Output dataset 'saved_reference' from step 40
True
200
0.0005
resolve
All
100
1.0
Step 202: TN93 Cluster
Output dataset 'output' from step 156
Output dataset 'saved_reference' from step 41
True
200
0.0005
resolve
All
100
1.0
Step 203: TN93 Cluster
Output dataset 'output' from step 157
Output dataset 'saved_reference' from step 42
True
200
0.0005
resolve
All
100
1.0
Step 204: TN93 Cluster
Output dataset 'output' from step 158
Output dataset 'saved_reference' from step 43
True
200
0.0005
resolve
All
100
1.0
Step 205: TN93 Cluster
Output dataset 'output' from step 159
Output dataset 'saved_reference' from step 44
True
200
0.0005
resolve
All
100
1.0
Step 206: TN93 Cluster
Output dataset 'output' from step 160
Output dataset 'saved_reference' from step 45
True
200
0.0005
resolve
All
100
1.0
Step 207: TN93 Cluster
Output dataset 'output' from step 161
Output dataset 'saved_reference' from step 46
True
200
0.0005
resolve
All
100
1.0
Step 208: TN93 Cluster
Output dataset 'output' from step 162
Output dataset 'saved_reference' from step 47
True
200
0.0005
resolve
All
100
1.0
Step 209: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 164
Output dataset 'saved_reference' from step 26
Output dataset 'tn93_compressed_clusters' from step 186
0.015
Step 210: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 163
Output dataset 'saved_reference' from step 25
Output dataset 'tn93_compressed_clusters' from step 187
0.015
Step 211: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 165
Output dataset 'saved_reference' from step 27
Output dataset 'tn93_compressed_clusters' from step 188
0.015
Step 212: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 166
Output dataset 'saved_reference' from step 28
Output dataset 'tn93_compressed_clusters' from step 189
0.015
Step 213: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 167
Output dataset 'saved_reference' from step 29
Output dataset 'tn93_compressed_clusters' from step 190
0.015
Step 214: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 168
Output dataset 'saved_reference' from step 30
Output dataset 'tn93_compressed_clusters' from step 191
0.015
Step 215: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 169
Output dataset 'saved_reference' from step 31
Output dataset 'tn93_compressed_clusters' from step 192
0.015
Step 216: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 170
Output dataset 'saved_reference' from step 32
Output dataset 'tn93_compressed_clusters' from step 193
0.015
Step 217: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 171
Output dataset 'saved_reference' from step 33
Output dataset 'tn93_compressed_clusters' from step 194
0.015
Step 218: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 172
Output dataset 'saved_reference' from step 34
Output dataset 'tn93_compressed_clusters' from step 195
0.015
Step 219: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 173
Output dataset 'saved_reference' from step 35
Output dataset 'tn93_compressed_clusters' from step 196
0.015
Step 220: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 174
Output dataset 'saved_reference' from step 36
Output dataset 'tn93_compressed_clusters' from step 197
0.015
Step 221: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 175
Output dataset 'saved_reference' from step 37
Output dataset 'tn93_compressed_clusters' from step 198
0.015
Step 222: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 176
Output dataset 'saved_reference' from step 38
Output dataset 'tn93_compressed_clusters' from step 199
0.015
Step 223: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 177
Output dataset 'saved_reference' from step 39
Output dataset 'tn93_compressed_clusters' from step 200
0.015
Step 224: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 178
Output dataset 'saved_reference' from step 40
Output dataset 'tn93_compressed_clusters' from step 201
0.015
Step 225: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 179
Output dataset 'saved_reference' from step 41
Output dataset 'tn93_compressed_clusters' from step 202
0.015
Step 226: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 180
Output dataset 'saved_reference' from step 42
Output dataset 'tn93_compressed_clusters' from step 203
0.015
Step 227: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 181
Output dataset 'saved_reference' from step 43
Output dataset 'tn93_compressed_clusters' from step 204
0.015
Step 228: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 182
Output dataset 'saved_reference' from step 44
Output dataset 'tn93_compressed_clusters' from step 205
0.015
Step 229: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 183
Output dataset 'saved_reference' from step 45
Output dataset 'tn93_compressed_clusters' from step 206
0.015
Step 230: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 184
Output dataset 'saved_reference' from step 46
Output dataset 'tn93_compressed_clusters' from step 207
0.015
Step 231: TN93 Filter
Output dataset 'tn93_compressed_clusters' from step 185
Output dataset 'saved_reference' from step 47
Output dataset 'tn93_compressed_clusters' from step 208
0.015
Step 232: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 209
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 233: HyPhy-Conv
Output dataset 'filtered_reference' from step 209
Universal code
False
Step 234: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 210
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 235: HyPhy-Conv
Output dataset 'filtered_reference' from step 210
Universal code
False
Step 236: HyPhy-Conv
Output dataset 'filtered_reference' from step 211
Universal code
False
Step 237: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 211
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 238: HyPhy-Conv
Output dataset 'filtered_reference' from step 212
Universal code
False
Step 239: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 212
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 240: HyPhy-Conv
Output dataset 'filtered_reference' from step 213
Universal code
False
Step 241: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 213
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 242: HyPhy-Conv
Output dataset 'filtered_reference' from step 214
Universal code
False
Step 243: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 214
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 244: HyPhy-Conv
Output dataset 'filtered_reference' from step 215
Universal code
False
Step 245: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 215
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 246: HyPhy-Conv
Output dataset 'filtered_reference' from step 216
Universal code
False
Step 247: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 216
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 248: HyPhy-Conv
Output dataset 'filtered_reference' from step 217
Universal code
False
Step 249: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 217
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 250: HyPhy-Conv
Output dataset 'filtered_reference' from step 218
Universal code
False
Step 251: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 218
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 252: HyPhy-Conv
Output dataset 'filtered_reference' from step 219
Universal code
False
Step 253: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 219
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 254: HyPhy-Conv
Output dataset 'filtered_reference' from step 220
Universal code
False
Step 255: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 220
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 256: HyPhy-Conv
Output dataset 'filtered_reference' from step 221
Universal code
False
Step 257: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 221
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 258: HyPhy-Conv
Output dataset 'filtered_reference' from step 222
Universal code
False
Step 259: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 222
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 260: HyPhy-Conv
Output dataset 'filtered_reference' from step 223
Universal code
False
Step 261: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 223
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 262: HyPhy-Conv
Output dataset 'filtered_reference' from step 224
Universal code
False
Step 263: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 224
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 264: HyPhy-Conv
Output dataset 'filtered_reference' from step 225
Universal code
False
Step 265: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 225
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 266: HyPhy-Conv
Output dataset 'filtered_reference' from step 226
Universal code
False
Step 267: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 226
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 268: HyPhy-Conv
Output dataset 'filtered_reference' from step 227
Universal code
False
Step 269: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 227
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 270: HyPhy-Conv
Output dataset 'filtered_reference' from step 228
Universal code
False
Step 271: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 228
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 272: HyPhy-Conv
Output dataset 'filtered_reference' from step 229
Universal code
False
Step 273: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 229
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 274: HyPhy-Conv
Output dataset 'filtered_reference' from step 230
Universal code
False
Step 275: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 230
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 276: HyPhy-Conv
Output dataset 'filtered_reference' from step 231
Universal code
False
Step 277: IQ-TREE
General options:
Output dataset 'filtered_reference' from step 231
True
DNA
select at runtime
select at runtime
Not available.
False
False
Likelihood mapping analysis:
Not available.
select at runtime
False
Modelling Parameters:
Automatic model selection:
False
(None)
Not available.
Empty.
nuclear
Empty.
Empty.
2
10
AIC
False
Empty.
select at runtime
Specifying substitution models:
False
Rate heterogeneity:
Empty.
False
Empty.
False
False
Partition model options:
select at runtime
False
select at runtime
Site-specific frequency model options:
select at runtime
Not available.
False
Tree Parameters:
Tree search parameters:
Not available.
100
20
5
100
6
0.5
False
False
select at runtime
Single branch tests:
Not available.
False
Not available.
Tree topology tests:
select at runtime
Not available.
False
False
Constructing consensus tree:
False
False
0.0
Not available.
select at runtime
Empty.
Computing Robinson-Foulds distance:
select at runtime
False
False
Generating random trees:
Not available.
False
False
False
False
Empty.
Bootstrap Parameters:
Ultrafast bootstrap parameters:
Not available.
False
False
1000
0.99
100
0.5
Empty.
False
Nonparametric bootstrap:
Not available.
False
False
Miscellaneous options:
Empty.
Step 278: Annotate
Output dataset 'treefile' from step 232
Output dataset 'tn93_compressed_clusters' from step 164
REFERENCE
${Branch label}
Step 279: Annotate
Output dataset 'treefile' from step 234
Output dataset 'tn93_compressed_clusters' from step 163
REFERENCE
${Branch label}
Step 280: Annotate
Output dataset 'treefile' from step 237
Output dataset 'tn93_compressed_clusters' from step 165
REFERENCE
${Branch label}
Step 281: Annotate
Output dataset 'treefile' from step 239
Output dataset 'tn93_compressed_clusters' from step 166
REFERENCE
${Branch label}
Step 282: Annotate
Output dataset 'treefile' from step 241
Output dataset 'tn93_compressed_clusters' from step 167
REFERENCE
${Branch label}
Step 283: Annotate
Output dataset 'treefile' from step 243
Output dataset 'tn93_compressed_clusters' from step 168
REFERENCE
${Branch label}
Step 284: Annotate
Output dataset 'treefile' from step 245
Output dataset 'tn93_compressed_clusters' from step 169
REFERENCE
${Branch label}
Step 285: Annotate
Output dataset 'treefile' from step 247
Output dataset 'tn93_compressed_clusters' from step 170
REFERENCE
${Branch label}
Step 286: Annotate
Output dataset 'treefile' from step 249
Output dataset 'tn93_compressed_clusters' from step 171
REFERENCE
${Branch label}
Step 287: Annotate
Output dataset 'treefile' from step 251
Output dataset 'tn93_compressed_clusters' from step 172
REFERENCE
${Branch label}
Step 288: Annotate
Output dataset 'treefile' from step 253
Output dataset 'tn93_compressed_clusters' from step 173
REFERENCE
${Branch label}
Step 289: Annotate
Output dataset 'treefile' from step 255
Output dataset 'tn93_compressed_clusters' from step 174
REFERENCE
${Branch label}
Step 290: Annotate
Output dataset 'treefile' from step 257
Output dataset 'tn93_compressed_clusters' from step 175
REFERENCE
${Branch label}
Step 291: Annotate
Output dataset 'treefile' from step 259
Output dataset 'tn93_compressed_clusters' from step 176
REFERENCE
${Branch label}
Step 292: Annotate
Output dataset 'treefile' from step 261
Output dataset 'tn93_compressed_clusters' from step 177
REFERENCE
${Branch label}
Step 293: Annotate
Output dataset 'treefile' from step 263
Output dataset 'tn93_compressed_clusters' from step 178
REFERENCE
${Branch label}
Step 294: Annotate
Output dataset 'treefile' from step 265
Output dataset 'tn93_compressed_clusters' from step 179
REFERENCE
${Branch label}
Step 295: Annotate
Output dataset 'treefile' from step 267
Output dataset 'tn93_compressed_clusters' from step 180
REFERENCE
${Branch label}
Step 296: Annotate
Output dataset 'treefile' from step 269
Output dataset 'tn93_compressed_clusters' from step 181
REFERENCE
${Branch label}
Step 297: Annotate
Output dataset 'treefile' from step 271
Output dataset 'tn93_compressed_clusters' from step 182
REFERENCE
${Branch label}
Step 298: Annotate
Output dataset 'treefile' from step 273
Output dataset 'tn93_compressed_clusters' from step 183
REFERENCE
${Branch label}
Step 299: Annotate
Output dataset 'treefile' from step 275
Output dataset 'tn93_compressed_clusters' from step 184
REFERENCE
${Branch label}
Step 300: Annotate
Output dataset 'treefile' from step 277
Output dataset 'tn93_compressed_clusters' from step 185
REFERENCE
${Branch label}
Step 301: HyPhy-SLAC
Output dataset 'filtered_reference' from step 209
Output dataset 'labeled_tree_int' from step 278
Universal code
Enter a branch label
${Branch label}
0.1
1
Step 302: HyPhy-RELAX
Output dataset 'filtered_reference' from step 209
Output dataset 'labeled_tree_clade' from step 278
Universal code
Minimal
${Branch label}
Reference
Specify values
250
10
3
3
True
False
Step 303: HyPhy-BGM
Output dataset 'filtered_reference' from step 209
Output dataset 'labeled_tree_int' from step 278
Nucleotide
Enter a branch label
${Branch label}
100000
10000
100
1
1
Step 304: HyPhy-PRIME
Output dataset 'filtered_reference' from step 209
Output dataset 'labeled_tree_int' from step 278
Universal code
Enter a branch label
${Branch label}
Atchley
0.1
False
Step 305: HyPhy-MEME
Output dataset 'filtered_reference' from step 209
Output dataset 'labeled_tree_full' from step 278
Universal code
Enter a branch label
${Branch label}
0.1
True
Step 306: HyPhy-MEME
Output dataset 'filtered_reference' from step 209
Output dataset 'labeled_tree_int' from step 278
Universal code
Enter a branch label
${Branch label}
0.1
False
Step 307: HyPhy-BUSTED
Output dataset 'filtered_reference' from step 209
Output dataset 'labeled_tree_clade' from step 278
Universal code
Enter a branch label
${Branch label}
Specify values
250
10
3
3
False
False
Step 308: HyPhy-FEL
Output dataset 'filtered_reference' from step 209
Output dataset 'labeled_tree_int' from step 278
Universal code
Enter a branch label
${Branch label}
0.1
Yes (recommended)
Step 309: HyPhy-FADE
Output dataset 'proteins' from step 233
Output dataset 'labeled_tree_clade' from step 278
Enter a branch label
${Branch label}
GTR - General time reversible model
0-th order Variational Bayes approximation
20
0.5
Step 310: HyPhy-CFEL
Output dataset 'filtered_reference' from step 209
Output dataset 'labeled_tree_clade' from step 278
Universal code
Branch sets
Branch set 1
${Branch label}
Branch set 2
Reference
False
0.05
0.2
Yes (recommended)
Step 311: HyPhy-BGM
Output dataset 'filtered_reference' from step 210
Output dataset 'labeled_tree_int' from step 279
Nucleotide
Enter a branch label
${Branch label}
100000
10000
100
1
1
Step 312: HyPhy-BUSTED
Output dataset 'filtered_reference' from step 210
Output dataset 'labeled_tree_clade' from step 279
Universal code
Enter a branch label
${Branch label}
Specify values
250
10
3
3
False
False
Step 313: HyPhy-SLAC
Output dataset 'filtered_reference' from step 210
Output dataset 'labeled_tree_int' from step 279
Universal code
Enter a branch label
${Branch label}
0.1
1
Step 314: HyPhy-CFEL
Output dataset 'filtered_reference' from step 210
Output dataset 'labeled_tree_clade' from step 279
Universal code
Branch sets
Branch set 1
${Branch label}
Branch set 2
Reference
False
0.05
0.2
Yes (recommended)
Step 315: HyPhy-FADE
Output dataset 'proteins' from step 235
Output dataset 'labeled_tree_clade' from step 279
Enter a branch label
${Branch label}
GTR - General time reversible model
0-th order Variational Bayes approximation
20
0.5
Step 316: HyPhy-RELAX
Output dataset 'filtered_reference' from step 210
Output dataset 'labeled_tree_clade' from step 279
Universal code
Minimal
${Branch label}
Reference
Specify values
250
10
3
3
True
False
Step 317: HyPhy-FEL
Output dataset 'filtered_reference' from step 210
Output dataset 'labeled_tree_int' from step 279
Universal code
Enter a branch label
${Branch label}
0.1
Yes (recommended)
Step 318: HyPhy-MEME
Output dataset 'filtered_reference' from step 210
Output dataset 'labeled_tree_int' from step 279
Universal code
Enter a branch label
${Branch label}
0.1
False
Step 319: HyPhy-MEME
Output dataset 'filtered_reference' from step 210
Output dataset 'labeled_tree_full' from step 279
Universal code
Enter a branch label
${Branch label}
0.1
True
Step 320: HyPhy-PRIME
Output dataset 'filtered_reference' from step 210
Output dataset 'labeled_tree_int' from step 279
Universal code
Enter a branch label
${Branch label}
Atchley
0.1
False
Step 321: HyPhy-SLAC
Output dataset 'filtered_reference' from step 211
Output dataset 'labeled_tree_int' from step 280
Universal code
Enter a branch label
${Branch label}
0.1
1
Step 322: HyPhy-RELAX
Output dataset 'filtered_reference' from step 211
Output dataset 'labeled_tree_clade' from step 280
Universal code
Minimal
${Branch label}
Reference
Specify values
250
10
3
3
True
False
Step 323: HyPhy-PRIME
Output dataset 'filtered_reference' from step 211
Output dataset 'labeled_tree_int' from step 280
Universal code
Enter a branch label
${Branch label}
Atchley
0.1
False
Step 324: HyPhy-MEME
Output dataset 'filtered_reference' from step 211
Output dataset 'labeled_tree_full' from step 280
Universal code
Enter a branch label
${Branch label}
0.1
True
Step 325: HyPhy-MEME
Output dataset 'filtered_reference' from step 211
Output dataset 'labeled_tree_int' from step 280
Universal code
Enter a branch label
${Branch label}
0.1
False
Step 326: HyPhy-BGM
Output dataset 'filtered_reference' from step 211
Output dataset 'labeled_tree_int' from step 280
Nucleotide
Enter a branch label
${Branch label}
100000
10000
100
1
1
Step 327: HyPhy-FEL
Output dataset 'filtered_reference' from step 211
Output dataset 'labeled_tree_int' from step 280
Universal code
Enter a branch label
${Branch label}
0.1
Yes (recommended)
Step 328: HyPhy-BUSTED
Output dataset 'filtered_reference' from step 211
Output dataset 'labeled_tree_clade' from step 280
Universal code
Enter a branch label
${Branch label}
Specify values
250
10
3
3
False
False
Step 329: HyPhy-FADE
Output dataset 'proteins' from step 236
Output dataset 'labeled_tree_clade' from step 280
Enter a branch label
${Branch label}
GTR - General time reversible model
0-th order Variational Bayes approximation
20
0.5
Step 330: HyPhy-CFEL
Output dataset 'filtered_reference' from step 211
Output dataset 'labeled_tree_clade' from step 280
Universal code
Branch sets
Branch set 1
${Branch label}
Branch set 2
Reference
False
0.05
0.2
Yes (recommended)
Step 331: HyPhy-SLAC
Output dataset 'filtered_reference' from step 212
Output dataset 'labeled_tree_int' from step 281
Universal code
Enter a branch label
${Branch label}
0.1
1
Step 332: HyPhy-RELAX
Output dataset 'filtered_reference' from step 212
Output dataset 'labeled_tree_clade' from step 281
Universal code
Minimal
${Branch label}
Reference
Specify values
250
10
3
3
True
False
Step 333: HyPhy-PRIME
Output dataset 'filtered_reference' from step 212
Output dataset 'labeled_tree_int' from step 281
Universal code
Enter a branch label
${Branch label}
Atchley
0.1
False
Step 334: HyPhy-MEME
Output dataset 'filtered_reference' from step 212
Output dataset 'labeled_tree_full' from step 281
Universal code
Enter a branch label
${Branch label}
0.1
True
Step 335: HyPhy-MEME
Output dataset 'filtered_reference' from step 212
Output dataset 'labeled_tree_int' from step 281
Universal code
Enter a branch label
${Branch label}
0.1
False
Step 336: HyPhy-FEL
Output dataset 'filtered_reference' from step 212
Output dataset 'labeled_tree_int' from step 281
Universal code
Enter a branch label
${Branch label}
0.1
Yes (recommended)
Step 337: HyPhy-BGM
Output dataset 'filtered_reference' from step 212
Output dataset 'labeled_tree_int' from step 281
Nucleotide
Enter a branch label
${Branch label}
100000
10000
100
1
1
Step 338: HyPhy-FADE
Output dataset 'proteins' from step 238
Output dataset 'labeled_tree_clade' from step 281
Enter a branch label
${Branch label}
GTR - General time reversible model
0-th order Variational Bayes approximation
20
0.5
Step 339: HyPhy-BUSTED
Output dataset 'filtered_reference' from step 212
Output dataset 'labeled_tree_clade' from step 281
Universal code
Enter a branch label
${Branch label}
Specify values
250
10
3
3
False
False
Step 340: HyPhy-CFEL
Output dataset 'filtered_reference' from step 212
Output dataset 'labeled_tree_clade' from step 281
Universal code
Branch sets
Branch set 1
${Branch label}
Branch set 2
Reference
False
0.05
0.2
Yes (recommended)
Step 341: HyPhy-SLAC
Output dataset 'filtered_reference' from step 213
Output dataset 'labeled_tree_int' from step 282
Universal code
Enter a branch label
${Branch label}
0.1
1
Step 342: HyPhy-RELAX
Output dataset 'filtered_reference' from step 213
Output dataset 'labeled_tree_clade' from step 282
Universal code
Minimal
${Branch label}
Reference
Specify values
250
10
3
3
True
False
Step 343: HyPhy-PRIME
Output dataset 'filtered_reference' from step 213
Output dataset 'labeled_tree_int' from step 282
Universal code
Enter a branch label
${Branch label}
Atchley
0.1
False
Step 344: HyPhy-MEME
Output dataset 'filtered_reference' from step 213
Output dataset 'labeled_tree_full' from step 282
Universal code
Enter a branch label
${Branch label}
0.1
True
Step 345: HyPhy-MEME
Output dataset 'filtered_reference' from step 213
Output dataset 'labeled_tree_int' from step 282
Universal code
Enter a branch label
${Branch label}
0.1
False
Step 346: HyPhy-FEL
Output dataset 'filtered_reference' from step 213
Output dataset 'labeled_tree_int' from step 282
Universal code
Enter a branch label
${Branch label}
0.1
Yes (recommended)
Step 347: HyPhy-BGM
Output dataset 'filtered_reference' from step 213
Output dataset 'labeled_tree_int' from step 282
Nucleotide
Enter a branch label
${Branch label}
100000
10000
100
1
1
Step 348: HyPhy-FADE
Output dataset 'proteins' from step 240
Output dataset 'labeled_tree_clade' from step 282
Enter a branch label
${Branch label}
GTR - General time reversible model
0-th order Variational Bayes approximation
20
0.5
Step 349: HyPhy-BUSTED
Output dataset 'filtered_reference' from step 213
Output dataset 'labeled_tree_clade' from step 282
Universal code
Enter a branch label
${Branch label}
Specify values
250
10
3
3
False
False
Step 350: HyPhy-CFEL
Output dataset 'filtered_reference' from step 213
Output dataset 'labeled_tree_clade' from step 282
Universal code
Branch sets
Branch set 1
${Branch label}
Branch set 2
Reference
False
0.05
0.2
Yes (recommended)
Step 351: HyPhy-SLAC
Output dataset 'filtered_reference' from step 214
Output dataset 'labeled_tree_int' from step 283
Universal code
Enter a branch label
${Branch label}
0.1
1
Step 352: HyPhy-RELAX
Output dataset 'filtered_reference' from step 214
Output dataset 'labeled_tree_clade' from step 283
Universal code
Minimal
${Branch label}
Reference
Specify values
250
10
3
3
True
False
Step 353: HyPhy-PRIME
Output dataset 'filtered_reference' from step 214
Output dataset 'labeled_tree_int' from step 283
Universal code
Enter a branch label
${Branch label}
Atchley
0.1
False
Step 354: HyPhy-MEME
Output dataset 'filtered_reference' from step 214
Output dataset 'labeled_tree_full' from step 283
Universal code
Enter a branch label
${Branch label}
0.1
True
Step 355: HyPhy-MEME
Output dataset 'filtered_reference' from step 214
Output dataset 'labeled_tree_int' from step 283
Universal code
Enter a branch label
${Branch label}
0.1
False
Step 356: HyPhy-FEL
Output dataset 'filtered_reference' from step 214
Output dataset 'labeled_tree_int' from step 283
Universal code
Enter a branch label
${Branch label}
0.1
Yes (recommended)
Step 357: HyPhy-FADE
Output dataset 'proteins' from step 242
Output dataset 'labeled_tree_clade' from step 283
Enter a branch label
${Branch label}
GTR - General time reversible model
0-th order Variational Bayes approximation
20
0.5
Step 358: HyPhy-BGM
Output dataset 'filtered_reference' from step 214
Output dataset 'labeled_tree_int' from step 283
Nucleotide
Enter a branch label
${Branch label}
100000
10000
100
1
1
Step 359: HyPhy-BUSTED
Output dataset 'filtered_reference' from step 214
Output dataset 'labeled_tree_clade' from step 283
Universal code
Enter a branch label
${Branch label}
Specify values
250
10
3
3
False
False
Step 360: HyPhy-CFEL
Output dataset 'filtered_reference' from step 214
Output dataset 'labeled_tree_clade' from step 283
Universal code
Branch sets
Branch set 1
${Branch label}
Branch set 2
Reference
False
0.05
0.2
Yes (recommended)
Step 361: HyPhy-SLAC
Output dataset 'filtered_reference' from step 215
Output dataset 'labeled_tree_int' from step 284
Universal code
Enter a branch label
${Branch label}
0.1
1
Step 362: HyPhy-RELAX
Output dataset 'filtered_reference' from step 215
Output dataset 'labeled_tree_clade' from step 284
Universal code
Minimal
${Branch label}
Reference
Specify values
250
10
3
3
True
False
Step 363: HyPhy-PRIME
Output dataset 'filtered_reference' from step 215
Output dataset 'labeled_tree_int' from step 284
Universal code
Enter a branch label
${Branch label}
Atchley
0.1
False
Step 364: HyPhy-MEME
Output dataset 'filtered_reference' from step 215
Output dataset 'labeled_tree_full' from step 284
Universal code
Enter a branch label
${Branch label}
0.1
True
Step 365: HyPhy-MEME
Output dataset 'filtered_reference' from step 215
Output dataset 'labeled_tree_int' from step 284
Universal code
Enter a branch label
${Branch label}
0.1
False
Step 366: HyPhy-FEL
Output dataset 'filtered_reference' from step 215
Output dataset 'labeled_tree_int' from step 284
Universal code
Enter a branch label
${Branch label}
0.1
Yes (recommended)
Step 367: HyPhy-FADE
Output dataset 'proteins' from step 244
Output dataset 'labeled_tree_clade' from step 284
Enter a branch label
${Branch label}
GTR - General time reversible model
0-th order Variational Bayes approximation
20
0.5
Step 368: HyPhy-BGM
Output dataset 'filtered_reference' from step 215
Output dataset 'labeled_tree_int' from step 284
Nucleotide
Enter a branch label
${Branch label}
100000
10000
100
1
1
Step 369: HyPhy-BUSTED
Output dataset 'filtered_reference' from step 215
Output dataset 'labeled_tree_clade' from step 284
Universal code
Enter a branch label
${Branch label}
Specify values
250
10
3
3
False
False
Step 370: HyPhy-CFEL
Output dataset 'filtered_reference' from step 215
Output dataset 'labeled_tree_clade' from step 284
Universal code
Branch sets
Branch set 1
${Branch label}
Branch set 2
Reference
False
0.05
0.2
Yes (recommended)
Step 371: HyPhy-SLAC
Output dataset 'filtered_reference' from step 216
Output dataset 'labeled_tree_int' from step 285
Universal code
Enter a branch label
${Branch label}
0.1
1
Step 372: HyPhy-RELAX
Output dataset 'filtered_reference' from step 216
Output dataset 'labeled_tree_clade' from step 285
Universal code
Minimal
${Branch label}
Reference
Specify values
250
10
3
3
True
False
Step 373: HyPhy-PRIME
Output dataset 'filtered_reference' from step 216
Output dataset 'labeled_tree_int' from step 285
Universal code
Enter a branch label
${Branch label}
Atchley
0.1
False
Step 374: HyPhy-MEME
Output dataset 'filtered_reference' from step 216
Output dataset 'labeled_tree_full' from step 285
Universal code
Enter a branch label
${Branch label}
0.1
True
Step 375: HyPhy-MEME
Output dataset 'filtered_reference' from step 216
Output dataset 'labeled_tree_int' from step 285
Universal code
Enter a branch label
${Branch label}
0.1
False
Step 376: HyPhy-FEL
Output dataset 'filtered_reference' from step 216
Output dataset 'labeled_tree_int' from step 285
Universal code
Enter a branch label
${Branch label}
0.1
Yes (recommended)
Step 377: HyPhy-FADE
Output dataset 'proteins' from step 246
Output dataset 'labeled_tree_clade' from step 285
Enter a branch label
${Branch label}
GTR - General time reversible model
0-th order Variational Bayes approximation
20
0.5
Step 378: HyPhy-BGM
Output dataset 'filtered_reference' from step 216
Output dataset 'labeled_tree_int' from step 285
Nucleotide
Enter a branch label
${Branch label}
100000
10000
100
1
1
Step 379: HyPhy-BUSTED
Output dataset 'filtered_reference' from step 216
Output dataset 'labeled_tree_clade' from step 285
Universal code
Enter a branch label
${Branch label}
Specify values
250
10
3
3
False
False
Step 380: HyPhy-CFEL
Output dataset 'filtered_reference' from step 216
Output dataset 'labeled_tree_clade' from step 285
Universal code
Branch sets
Branch set 1
${Branch label}
Branch set 2
Reference
False
0.05
0.2
Yes (recommended)
Step 381: HyPhy-SLAC
Output dataset 'filtered_reference' from step 217
Output dataset 'labeled_tree_int' from step 286
Universal code
Enter a branch label
${Branch label}
0.1
1
Step 382: HyPhy-RELAX
Output dataset 'filtered_reference' from step 217
Output dataset 'labeled_tree_clade' from step 286
Universal code
Minimal
${Branch label}
Reference
Specify values
250
10
3
3
True
False
Step 383: HyPhy-PRIME
Output dataset 'filtered_reference' from step 217
Output dataset 'labeled_tree_int' from step 286
Universal code
Enter a branch label
${Branch label}
Atchley
0.1
False
Step 384: HyPhy-MEME
Output dataset 'filtered_reference' from step 217
Output dataset 'labeled_tree_full' from step 286
Universal code
Enter a branch label
${Branch label}
0.1
True
Step 385: HyPhy-MEME
Output dataset 'filtered_reference' from step 217
Output dataset 'labeled_tree_int' from step 286
Universal code
Enter a branch label
${Branch label}
0.1
False
Step 386: HyPhy-FEL
Output dataset 'filtered_reference' from step 217
Output dataset 'labeled_tree_int' from step 286
Universal code
Enter a branch label
${Branch label}
0.1
Yes (recommended)
Step 387: HyPhy-FADE
Output dataset 'proteins' from step 248
Output dataset 'labeled_tree_clade' from step 286
Enter a branch label
${Branch label}
GTR - General time reversible model
0-th order Variational Bayes approximation
20
0.5
Step 388: HyPhy-BGM
Output dataset 'filtered_reference' from step 217
Output dataset 'labeled_tree_int' from step 286
Nucleotide
Enter a branch label
${Branch label}
100000
10000
100
1
1
Step 389: HyPhy-BUSTED
Output dataset 'filtered_reference' from step 217
Output dataset 'labeled_tree_clade' from step 286
Universal code
Enter a branch label
${Branch label}
Specify values
250
10
3
3
False
False
Step 390: HyPhy-CFEL
Output dataset 'filtered_reference' from step 217
Output dataset 'labeled_tree_clade' from step 286
Universal code
Branch sets
Branch set 1
${Branch label}
Branch set 2
Reference
False
0.05
0.2
Yes (recommended)
Step 391: HyPhy-SLAC
Output dataset 'filtered_reference' from step 218
Output dataset 'labeled_tree_int' from step 287
Universal code
Enter a branch label
${Branch label}
0.1
1
Step 392: HyPhy-RELAX
Output dataset 'filtered_reference' from step 218
Output dataset 'labeled_tree_clade' from step 287
Universal code
Minimal
${Branch label}
Reference
Specify values
250
10
3
3
True
False
Step 393: HyPhy-PRIME
Output dataset 'filtered_reference' from step 218
Output dataset 'labeled_tree_int' from step 287
Universal code
Enter a branch label
${Branch label}
Atchley
0.1
False
Step 394: HyPhy-MEME
Output dataset 'filtered_reference' from step 218
Output dataset 'labeled_tree_full' from step 287
Universal code
Enter a branch label
${Branch label}
0.1
True
Step 395: HyPhy-MEME
Output dataset 'filtered_reference' from step 218
Output dataset 'labeled_tree_int' from step 287
Universal code
Enter a branch label
${Branch label}
0.1
False
Step 396: HyPhy-FEL
Output dataset 'filtered_reference' from step 218
Output dataset 'labeled_tree_int' from step 287
Universal code
Enter a branch label
${Branch label}
0.1
Yes (recommended)
Step 397: HyPhy-FADE
Output dataset 'proteins' from step 250
Output dataset 'labeled_tree_clade' from step 287
Enter a branch label
${Branch label}
GTR - General time reversible model
0-th order Variational Bayes approximation
20
0.5
Step 398: HyPhy-BGM
Output dataset 'filtered_reference' from step 218
Output dataset 'labeled_tree_int' from step 287
Nucleotide
Enter a branch label
${Branch label}
100000
10000
100
1
1
Step 399: HyPhy-BUSTED
Output dataset 'filtered_reference' from step 218
Output dataset 'labeled_tree_clade' from step 287
Universal code
Enter a branch label
${Branch label}
Specify values
250
10
3
3
False
False
Step 400: HyPhy-CFEL
Output dataset 'filtered_reference' from step 218
Output dataset 'labeled_tree_clade' from step 287
Universal code
Branch sets
Branch set 1
${Branch label}
Branch set 2
Reference
False
0.05
0.2
Yes (recommended)
Step 401: HyPhy-SLAC
Output dataset 'filtered_reference' from step 219
Output dataset 'labeled_tree_int' from step 288
Universal code
Enter a branch label
${Branch label}
0.1
1
Step 402: HyPhy-RELAX
Output dataset 'filtered_reference' from step 219
Output dataset 'labeled_tree_clade' from step 288
Universal code
Minimal
${Branch label}
Reference
Specify values
250
10
3
3
True
False
Step 403: HyPhy-PRIME
Output dataset 'filtered_reference' from step 219
Output dataset 'labeled_tree_int' from step 288
Universal code
Enter a branch label
${Branch label}
Atchley
0.1
False
Step 404: HyPhy-MEME
Output dataset 'filtered_reference' from step 219
Output dataset 'labeled_tree_full' from step 288
Universal code
Enter a branch label
${Branch label}
0.1
True
Step 405: HyPhy-MEME
Output dataset 'filtered_reference' from step 219
Output dataset 'labeled_tree_int' from step 288
Universal code
Enter a branch label
${Branch label}
0.1
False
Step 406: HyPhy-FEL
Output dataset 'filtered_reference' from step 219
Output dataset 'labeled_tree_int' from step 288
Universal code
Enter a branch label
${Branch label}
0.1
Yes (recommended)
Step 407: HyPhy-FADE
Output dataset 'proteins' from step 252
Output dataset 'labeled_tree_clade' from step 288
Enter a branch label
${Branch label}
GTR - General time reversible model
0-th order Variational Bayes approximation
20
0.5
Step 408: HyPhy-BGM
Output dataset 'filtered_reference' from step 219
Output dataset 'labeled_tree_int' from step 288
Nucleotide
Enter a branch label
${Branch label}
100000
10000
100
1
1
Step 409: HyPhy-BUSTED
Output dataset 'filtered_reference' from step 219
Output dataset 'labeled_tree_clade' from step 288
Universal code
Enter a branch label
${Branch label}
Specify values
250
10
3
3
False
False
Step 410: HyPhy-CFEL
Output dataset 'filtered_reference' from step 219
Output dataset 'labeled_tree_clade' from step 288
Universal code
Branch sets
Branch set 1
${Branch label}
Branch set 2
Reference
False
0.05
0.2
Yes (recommended)
Step 411: HyPhy-SLAC
Output dataset 'filtered_reference' from step 220
Output dataset 'labeled_tree_int' from step 289
Universal code
Enter a branch label
${Branch label}
0.1
1
Step 412: HyPhy-RELAX
Output dataset 'filtered_reference' from step 220
Output dataset 'labeled_tree_clade' from step 289
Universal code
Minimal
${Branch label}
Reference
Specify values
250
10
3
3
True
False
Step 413: HyPhy-PRIME
Output dataset 'filtered_reference' from step 220
Output dataset 'labeled_tree_int' from step 289
Universal code
Enter a branch label
${Branch label}
Atchley
0.1
False
Step 414: HyPhy-MEME
Output dataset 'filtered_reference' from step 220
Output dataset 'labeled_tree_full' from step 289
Universal code
Enter a branch label
${Branch label}
0.1
True
Step 415: HyPhy-MEME
Output dataset 'filtered_reference' from step 220
Output dataset 'labeled_tree_int' from step 289
Universal code
Enter a branch label
${Branch label}
0.1
False
Step 416: HyPhy-FEL
Output dataset 'filtered_reference' from step 220
Output dataset 'labeled_tree_int' from step 289
Universal code
Enter a branch label
${Branch label}
0.1
Yes (recommended)
Step 417: HyPhy-FADE
Output dataset 'proteins' from step 254
Output dataset 'labeled_tree_clade' from step 289
Enter a branch label
${Branch label}
GTR - General time reversible model
0-th order Variational Bayes approximation
20
0.5
Step 418: HyPhy-BGM
Output dataset 'filtered_reference' from step 220
Output dataset 'labeled_tree_int' from step 289
Nucleotide
Enter a branch label
${Branch label}
100000
10000
100
1
1
Step 419: HyPhy-BUSTED
Output dataset 'filtered_reference' from step 220
Output dataset 'labeled_tree_clade' from step 289
Universal code
Enter a branch label
${Branch label}
Specify values
250
10
3
3
False
False
Step 420: HyPhy-CFEL
Output dataset 'filtered_reference' from step 220
Output dataset 'labeled_tree_clade' from step 289
Universal code
Branch sets
Branch set 1
${Branch label}
Branch set 2
Reference
False
0.05