Explore Workflows
View already parsed workflows here or click here to add your own
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Tumor-Only Detect Variants workflow
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![]() Path: definitions/pipelines/tumor_only_detect_variants.cwl Branch/Commit ID: f21b6c6f70f01d0fe08193684060161107f0bf59 |
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count-lines12-wf.cwl
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![]() Path: cwltool/schemas/v1.0/v1.0/count-lines12-wf.cwl Branch/Commit ID: e4a52682f3bdefafe5c27e32983fed31116ac489 |
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directory.cwl
Inspect provided directory and return filenames. Generate a new directory and return it (including content). |
![]() Path: tests/wf/directory.cwl Branch/Commit ID: e62a8406b448220969ee172699f61c5ca379d60c |
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tt_kmer_compare_wnode
Pairwise comparison |
![]() Path: task_types/tt_kmer_compare_wnode.cwl Branch/Commit ID: e0fb04a0d8bc648183c6b71d099ce7aea3c3b3ff |
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schemadef-wf.cwl
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![]() Path: cwltool/schemas/v1.0/v1.0/schemadef-wf.cwl Branch/Commit ID: 4a31f2a1c1163492ae37bbc748a299e8318c462c |
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BWA index pipeline
This workflow indexes the input reference FASTA with bwa, and generates faidx and dict file using samtools. This index sample can then be used as input into the germline variant calling workflow, or others that may include this workflow as an upstream source. ### __Inputs__ - FASTA file of the reference genome that will be indexed. ### __Outputs__ - Directory containing the original FASTA, faidx, dict, and bwa index files. - stdout log file (output in Overview tab as well) - stderr log file ### __Data Analysis Steps__ 1. cwl calls dockercontainer robertplayer/scidap-gatk4 to index reference FASTA with bwa, and generates faidx and dict files using samtools ### __References__ - Li, H., & Durbin, R. (2009). Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics, 25(14), 1754–1760. |
![]() Path: workflows/bwa-index.cwl Branch/Commit ID: b4d578c2ba4713a5a22163d9f8c7105acda1f22e |
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Chipseq alignment for mouse with qc and creating homer tag directory
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![]() Path: definitions/pipelines/chipseq_alignment_mouse.cwl Branch/Commit ID: 038cb3617a1966a1057386adcde97ce55d9e1139 |
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Chipseq alignment with qc and creating homer tag directory
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![]() Path: definitions/pipelines/chipseq.cwl Branch/Commit ID: 457e101e3fb87e7fd792357afce00ed8ccbfbcdb |
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taxonomy_check_16S
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![]() Path: task_types/tt_taxonomy_check_16S.cwl Branch/Commit ID: 89098668413e90519c99b35143bffec509d3599c |
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RNA-Seq pipeline single-read stranded mitochondrial
Slightly changed original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for **strand specific single-read** experiment. An additional steps were added to map data to mitochondrial chromosome only and then merge the output. Experiment files in [FASTQ](http://maq.sourceforge.net/fastq.shtml) format either compressed or not can be used. Current workflow should be used only with single-read strand specific RNA-Seq data. It performs the following steps: 1. `STAR` to align reads from input FASTQ file according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 2. `fastx_quality_stats` to analyze input FASTQ file and generate quality statistics file 3. `samtools sort` to generate coordinate sorted BAM(+BAI) file pair from the unsorted BAM file obtained on the step 1 (after running STAR) 5. Generate BigWig file on the base of sorted BAM file 6. Map input FASTQ file to predefined rRNA reference indices using Bowtie to define the level of rRNA contamination; export resulted statistics to file 7. Calculate isoform expression level for the sorted BAM file and GTF/TAB annotation file using `GEEP` reads-counting utility; export results to file |
![]() Path: workflows/rnaseq-se-dutp-mitochondrial.cwl Branch/Commit ID: e9a24699d8b5ffe64412b1ba0af8448c281b223a |