Galaxy | Accessible Workflow | Human SAP DB / UMN

Human SAP DB Workflow

Galaxy Workflow 'Human SAP DB'

Annotation: The SAP Database Workflow creates a database of polypeptide sequences containing single amino acid polymorphisms (SAPs) detected in RNA-Seq data.

Step	Annotation
Step 1: Input dataset RNA-Seq Left mate pair fastq select at runtime	RNA-Seq left mate pair fastq (These should be in fastqsanger format. If not, convert with "Fastq Groomer" tool.)
Step 2: Input dataset RNA-Seq right mate pair fastq select at runtime	RNA-Seq right mate pair fastq (These should be in fastqsanger format. If not, convert with "Fastq Groomer" tool.)
Step 3: Input dataset Ensembl GTF for the reference genome select at runtime	Homo_sapiens.GRCh37_canon.73.gtf
Step 4: Input dataset The Ensembl peptide sequences fasta select at runtime	Homo_sapiens.GRCh37.73.pep.all.fa
Step 5: Select first Select first 100000 from Output dataset 'output' from step 1	Limit the sequence count for demonstration and testing purposes (100000)
Step 6: Select first Select first 100000 from Output dataset 'output' from step 2	Limit the sequence count for demonstration and testing purposes (100000)
Step 7: Convert GFF to BED Choose GFF file Output dataset 'output' from step 3	Convert GTF file (in GFF or GTF format) to BED format for use in Mpileup.
Step 8: Tophat for Illumina RNA-Seq FASTQ file Output dataset 'out_file1' from step 5 Use a built in reference genome or own from your history Use a built-in genome Select a reference genome GRCh37_canon Is this library mate-paired? Paired-end RNA-Seq FASTQ file Output dataset 'out_file1' from step 6 Mean Inner Distance between Mate Pairs 150 TopHat settings to use Full parameter list Library Type FR Unstranded Std. Dev for Distance between Mate Pairs 20 Anchor length (at least 3) 5 Maximum number of mismatches that can appear in the anchor region of spliced alignment 0 The minimum intron length 70 The maximum intron length 500000 Allow indel search Yes Max insertion length. 3 Max deletion length. 3 Maximum number of alignments to be allowed 20 Minimum intron length that may be found during split-segment (default) search 50 Maximum intron length that may be found during split-segment (default) search 500000 Number of mismatches allowed in the initial read mapping 2 Number of mismatches allowed in each segment alignment for reads mapped independently 2 Minimum length of read segments 25 Use Own Junctions Yes Use Gene Annotation Model Yes Gene Model Annotations Output dataset 'output' from step 3 Use Raw Junctions No Only look for supplied junctions Yes Use Closure Search No Use Coverage Search No Use Microexon Search No	GTF-guided alignment of reads using Tophat.
Step 9: MPileup Choose the source for the reference list Locally cached BAM files BAM file 1 BAM file Output dataset 'accepted_hits' from step 8 Using reference genome GRCh37_canon Genotype Likelihood Computation Perform genotype likelihood computation Phred-scaled gap extension sequencing error probability 20 Coefficient for modeling homopolymer errors. 100 Perform INDEL calling Do not perform INDEL calling Phred-scaled gap open sequencing error probability 40 Platform for INDEL candidates Set advanced options Advanced Do not skip anomalous read pairs in variant calling False Disable probabilistic realignment for the computation of base alignment quality (BAQ) False Coefficient for downgrading mapping quality for reads containing excessive mismatches 0 Max reads per BAM 250 Extended BAQ computation False List of regions or sites on which to operate Output dataset 'output1' from step 7 Minimum mapping quality for an alignment to be used 0 Minimum base quality for a base to be considered 13 Only generate pileup in region Output per-sample read depth True Output per-sample Phred-scaled strand bias P-value False	SAMtool's MPileup command to call SNPs within protein coding regions.
Step 10: bcftools view Choose a bcf file to view Output dataset 'output_mpileup' from step 9 Retain all possible alternate alleles at variant sites Yes Output in the BCF format. The default is VCF. No Sequence dictionary (list of chromosome names) for VCF->BCF conversion. No Indicate PL is generated by r921 or before (ordering is different). No Suppress all individual genotype information. No Skip sites where the REF field is not A/C/G/T No The input is VCF instead of BCF. No Uncompressed BCF output. No Call variants using Bayesian inference. Automatically performs max-likelihood inference only Yes Perform max-likelihood inference only, including estimating the site allele frequency, testing Hardy-Weinberg equilibrium and testing associations with LRT. No Call per-sample genotypes at variant sites No Use alternate INDEL-to-SNP mutation rate, default 0.15. No variant_filter No Specify scaled mutation rate for variant calling, default is 0.001. No Output variant sites only. Yes	Convert binary call format (BCF) to variant call format (VCF).
Step 11: SnpEff Sequence changes (SNPs, MNPs, InDels) Output dataset 'output' from step 10 Input format VCF Output format VCF (only if input is VCF) Genome source Named on demand Snpff Version Name GRCh37.73 Upstream / Downstream length No upstream / downstream intervals (0 bases) Set size for splice sites (donor and acceptor) in bases 1 base Filter homozygous / heterozygous changes No filter (analyze everything) Filter sequence changes Only SNPs (single nucleotide polymorphisms) Annotation options Use custom interval file for annotation select at runtime Only use the transcripts in this file. select at runtime Filter output Do not show DOWNSTREAM changes Do not show INTERGENIC changes Do not show INTRON changes Do not show UPSTREAM changes Do not show 5_PRIME_UTR or 3_PRIME_UTR changes Chromosomal position Use default (based on input type) Text to prepend to chromosome name Produce Summary Stats True Do not report usage statistics to server True	SnpEff to annotate detected SNPs that correspond to protein-level amino acid polymorphisms (SAPs). ( Set genome version: GRCh37.73 )
Step 12: SnpEff to Peptide fasta SnpEff generated VCF file with NON_SYNONYMOUS_CODING annotations Output dataset 'snpeff_output' from step 11 Ensembl all_pep.fa Output dataset 'output' from step 4 Preceeding AAs 66 Following AAs 66	Translate nucleotide sequences with SNPs into peptide sequences with the Single Amino Acid Polymorphisms (SAPs). Compile into a customized SAP database compatible with MS database searching strategies.