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EMS Mutagenesis Backcross Mutation Caller

Step	Annotation
Step 1: Input dataset ce11.fa.gz select at runtime
Step 2: Input dataset collection input select at runtime
Step 3: fastp Single-end or paired reads Paired Collection Select paired collection(s) Output dataset 'output' from step 2 Adapter Trimming Options: Disable adapter trimming False Adapter sequence for input 1 Empty. Adapter sequence for input 2 Empty. Global trimming options: Trim front for input 1 Not available. Trim tail for input 1 Not available. Trim front for input 2 Not available. Trim tail for input 2 Not available. Overrepresented Sequence Analysis: Enable overrepresented analysis True Overrepresentation sampling Not available. Filter Options: Quality filtering options: Disable quality filtering False Qualified quality phred Not available. Unqualified percent limit Not available. N base limit Not available. Length filtering options: Disable length filtering False Length required Not available. Maximum length Not available. Low complexity filtering options: Enable low complexity filter False Complexity threshold Not available. Read Modification Options: PolyG tail trimming Automatic trimming for Illumina NextSeq/NovaSeq data PolyG minimum length Not available. PolyX tail trimming Disable polyX trimming UMI processing: Enable unique molecular identifer False UMI location Empty. UMI length Not available. UMI prefix Empty. Per read cutting by quality options: Cut by quality in front (5') False Cut by quality in tail (3') False Cutting window size Not available. Cutting mean quality Not available. Base correction by overlap analysis options: Enable base correction False Output Options: Output HTML report True Output JSON report True
Step 4: Apply rules Input Collection Output dataset 'output_paired_coll' from step 3 Rules Rules: - {'error': None, 'type': 'add_column_metadata', 'value': 'identifier0', 'warn': None} - {'error': None, 'type': 'add_column_metadata', 'value': 'identifier1', 'warn': None} - {'error': None, 'expression': '\\w+_(\\d+)_S\\d+_L\\d+.*', 'group_count': 1, 'target_column': 0, 'type': 'add_column_regex', 'warn': None} Column Definitions: - {'columns': [1], 'type': 'paired_identifier'} - {'columns': [2], 'editing': False, 'type': 'list_identifiers'}
Step 5: Unzip collection Paired input to unzip Output dataset 'output' from step 4
Step 6: FASTQ Groomer File to groom Output dataset 'reverse' from step 5 Input FASTQ quality scores type Sanger & Illumina 1.8+ Advanced Options Hide Advanced Options
Step 7: FASTQ Groomer File to groom Output dataset 'forward' from step 5 Input FASTQ quality scores type Sanger & Illumina 1.8+ Advanced Options Hide Advanced Options
Step 8: Bowtie2 Is this single or paired library Paired-end FASTA/Q file #1 Output dataset 'output_file' from step 7 FASTA/Q file #2 Output dataset 'output_file' from step 6 Write unaligned reads (in fastq format) to separate file(s) False Write aligned reads (in fastq format) to separate file(s) False Do you want to set paired-end options? Yes Set the minimum fragment length for valid paired-end alignments 0 Set the maximum fragment length for valid paired-end alignments 500 Select the upstream/downstream mate orientations for a valid paired-end alignment against the forward reference strand --fr Disable no-mixed behavior False Disable no-discordant behavior False Allow mate dovetailing False Disallow one mate alignment to contain another False Disallow mate alignments to overlap False Will you select a reference genome from your history or use a built-in index? Use a genome from the history and build index Select reference genome Output dataset 'output' from step 1 Set read groups information? Set read groups (SAM/BAM specification) Auto-assign True Auto-assign True Platform/technology used to produce the reads (PL) ILLUMINA Auto-assign False Library name (LB) Empty. Sequencing center that produced the read (CN) Empty. Description (DS) Empty. Date that run was produced (DT) Empty. Flow order (FO) Empty. The array of nucleotide bases that correspond to the key sequence of each read (KS) Empty. Programs used for processing the read group (PG) Empty. Predicted median insert size (PI) Not available. Platform unit (PU) Empty. Select analysis mode 1: Default setting only Do you want to use presets? Sensitive local (--sensitive-local) Do you want to tweak SAM/BAM Options? No Save the bowtie2 mapping statistics to the history True
Step 9: Samtools sort BAM File Output dataset 'output' from step 8 Primary sort key coordinate
Step 10: MarkDuplicates Select SAM/BAM dataset or dataset collection Output dataset 'output1' from step 9 Comments If true do not write duplicates to the output file instead of writing them with appropriate flags set True Assume the input file is already sorted True The scoring strategy for choosing the non-duplicate among candidates SUM_OF_BASE_QUALITIES Regular expression that can be used in unusual situations to parse non-standard read names in the incoming SAM/BAM dataset Empty. The maximum offset between two duplicte clusters in order to consider them optical duplicates 100 Barcode Tag Empty. Select validation stringency Lenient
Step 11: MiModD Variant Calling Will you select a reference genome from your history or use a built-in genome? Use a genome from my history reference genome Output dataset 'output' from step 1 Aligned reads input dataset(s) Output dataset 'outFile' from step 10 group reads based on read group id only False More options: md5 sum verification of contigs/chromosomes True average sample depth cap limit (default: 250) 250
Step 12: MultiQC Results Results 1 Which tool was used generate logs? fastp Output of fastp Output dataset 'report_json' from step 3 Results 2 Which tool was used generate logs? Bowtie 2 Output of Bowtie 2 Output dataset 'mapping_stats' from step 8 Results 3 Which tool was used generate logs? Picard Picard outputs Picard output 1 Type of Picard output? Markdups Picard output Output dataset 'metrics_file' from step 10 Report title QC data for raw fastqs, trimming (fastp), alignment (bowtie2), and deduplication (picard) Custom comment Empty. Use only flat plots (non-interactive images) False Output the multiQC log file? False
Step 13: MiModD Deletion Calling (for PE data) Aligned reads input dataset(s) Output dataset 'outFile' from step 10 BCF variant call dataset to extract coverage from Output dataset 'ofile' from step 11 group reads based on read group id only False include low-coverage regions False maximal coverage allowed inside a low-coverage region (default: 0) 4 minimal deletion size (default: 100) 100
Step 14: MiModD Extract Variant Sites BCF input file Output dataset 'ofile' from step 11 include information from pre-calculated vcf datasets keep all sites with alternate bases False
Step 15: SnpSift Variant Type Variant file (VCF) Output dataset 'output_vcf' from step 14

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richardjacton

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