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ASaiM - Metagenomic assembly with MetaSPAdes

Step	Annotation
Step 1: Input dataset Mate 1 select at runtime
Step 2: Input dataset Mate 2 select at runtime
Step 3: FastQC Short read data from your current history Output dataset 'output' from step 1 Contaminant list select at runtime Submodule and Limit specifing file select at runtime
Step 4: Trim Galore! Is this library paired- or single-end? Paired-end Reads in FASTQ format Output dataset 'output' from step 1 Reads in FASTQ format Output dataset 'output' from step 2 Adapter sequence to be trimmed Automatic detection Trims 1 bp off every read from its 3' end. False Remove N bp from the 3' end of read 1 Not available. Remove N bp from the 3' end of read 2 Not available. Trim Galore! advanced settings Full parameter list Trim low-quality ends from reads in addition to adapter removal (Enter phred quality score threshold) 20 Overlap with adapter sequence required to trim a sequence 1 Maximum allowed error rate 0.1 Discard reads that became shorter than length N 20 Instructs Trim Galore! to remove N bp from the 5' end of read 1 Not available. Instructs Trim Galore! to remove N bp from the 5' end of read 2 (Only for paired-end reads) Not available. Generate a report file True specify if you would like to retain unpaired reads Do not output unpaired reads RRBS specific settings Use defaults (no RRBS)
Step 5: FastQC Short read data from your current history Output dataset 'output' from step 2 Contaminant list select at runtime Submodule and Limit specifing file select at runtime
Step 6: metaSPAdes Run only assembly? (without read error correction) False Automatically choose k-mer values False K-mers to use, separated by commas 21,33,55 Library type Paired-end Orientation -> <- (fr) Files Files 1 Select file format Separate input files Forward reads Output dataset 'trimmed_reads_pair1' from step 4 Reverse reads Output dataset 'trimmed_reads_pair2' from step 4
Step 7: Quast Input assembly files Input assembly files 1 Contigs/scaffolds output file Output dataset 'out_contigs' from step 6 Type of data Contig Input assembly files 2 Contigs/scaffolds output file Output dataset 'out_scaffolds' from step 6 Type of data Scaffold Size of reference genome Not available. Reference File select at runtime Gene Annotations select at runtime Operon Annotations select at runtime Type of organism Metagenomes Lower Threshold 500 Thresholds 0,1000
Step 8: VALET Candidate assembly Candidate assemblies 1 Candidate assembly file Output dataset 'out_contigs' from step 6 Name of the assembly MetaSPAdes Type of input reads used for the assembly Paired Input format FastQ Mate pair reads Mate pair reads 1 Assembly input first mate reads Output dataset 'trimmed_reads_pair1' from step 4 Assembly input second mate reads Output dataset 'trimmed_reads_pair2' from step 4 Min insert sizes for mate pairs 0 Max insert sizes for mate pairs 500 Orientation of the mates fr: mate 1 appears upstream of the reverse complement of mate 2 or mate 2 appears upstream of the reverse complement of mate 1 Sliding window size when determining misassemblies 501 Bowtie2 parameter to set the max number of alignments 10000 Minimum average coverage to run misassembly detection 0 When binning by coverage, the new high = high + high * multiplier 0.0 Minimum number of overlapping flagged miassemblies to mark region as suspicious 2 Mark region as suspicious if multiple signatures occur within this window size 2000 Ignore contigs smaller than this length 1000 Ignore flagged regions within b bps from the ends of the contigs 0 Bin sized used to find breakpoints 50 Kmer length used for abundance estimation 15 Assembly created per-contig coverage file select at runtime File containing ORFs select at runtime
Step 9: Bowtie2 Is this single or paired library Paired-end FASTA/Q file #1 Output dataset 'trimmed_reads_pair1' from step 4 FASTA/Q file #2 Output dataset 'trimmed_reads_pair2' from step 4 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? No 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 'out_contigs' from step 6 Set read groups information? Do not set Select analysis mode 1: Default setting only Do you want to use presets? No, just use defaults Save the bowtie2 mapping statistics to the history True
Step 10: MultiQC Results Results 1 Which tool was used generate logs? QUAST Output of Quast Output dataset 'quast_tsv' from step 7 Results 2 Which tool was used generate logs? Bowtie 2 Output of Bowtie 2 Output dataset 'mapping_stats' from step 9 Results 3 Which tool was used generate logs? FastQC FastQC outputs FastQC output 1 Type of FastQC output? Raw data FastQC output Output dataset 'text_file' from step 5,Output dataset 'text_file' from step 3 Results 4 Which tool was used generate logs? Cutadapt/Trim Galore! Output of Cutadapt Output dataset 'report_file' from step 4 Output the multiQC log file? False

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berenice

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