Explore Workflows

View already parsed workflows here or click here to add your own

Graph Name Retrieved From View
workflow graph somatic_exome: exome alignment and somatic variant detection

somatic_exome is designed to perform processing of mutant/wildtype H.sapiens exome sequencing data. It features BQSR corrected alignments, 4 caller variant detection, and vep style annotations. Structural variants are detected via manta and cnvkit. In addition QC metrics are run, including somalier concordance metrics. example input file = analysis_workflows/example_data/somatic_exome.yaml

https://github.com/tmooney/cancer-genomics-workflow.git

Path: definitions/pipelines/somatic_exome.cwl

Branch/Commit ID: downsample_and_recall
workflow graph functional analysis prediction with InterProScan

https://github.com/EBI-Metagenomics/ebi-metagenomics-cwl.git

Path: workflows/functional_analysis.cwl

Branch/Commit ID: f993cad
workflow graph collate_unique_SSU_headers.cwl

https://github.com/ProteinsWebTeam/ebi-metagenomics-cwl.git

Path: tools/collate_unique_SSU_headers.cwl

Branch/Commit ID: f993cad
workflow graph create_fig.cwl

https://github.com/jniestroy/cwl_parser.git

Path: workflows/create_fig.cwl

Branch/Commit ID: master
workflow graph EMG pipeline's QIIME workflow

Step 1: Set environment PYTHONPATH, QIIME_ROOT, PATH Step 2: Run QIIME script pick_closed_reference_otus.py ${python} ${qiimeDir}/bin/pick_closed_reference_otus.py -i $1 -o $2 -r ${qiimeDir}/gg_13_8_otus/rep_set/97_otus.fasta -t ${qiimeDir}/gg_13_8_otus/taxonomy/97_otu_taxonomy.txt -p ${qiimeDir}/cr_otus_parameters.txt Step 3: Convert new biom format to old biom format (json) ${qiimeDir}/bin/biom convert -i ${resultDir}/cr_otus/otu_table.biom -o ${resultDir}/cr_otus/${infileBase}_otu_table_json.biom --table-type=\"OTU table\" --to-json Step 4: Convert new biom format to a classic OTU table. ${qiimeDir}/bin/biom convert -i ${resultDir}/cr_otus/otu_table.biom -o ${resultDir}/cr_otus/${infileBase}_otu_table.txt --to-tsv --header-key taxonomy --table-type \"OTU table\" Step 5: Create otu summary ${qiimeDir}/bin/biom summarize-table -i ${resultDir}/cr_otus/otu_table.biom -o ${resultDir}/cr_otus/${infileBase}_otu_table_summary.txt Step 6: Move one of the result files mv ${resultDir}/cr_otus/otu_table.biom ${resultDir}/cr_otus/${infileBase}_otu_table_hdf5.biom Step 7: Create a list of observations awk '{print $1}' ${resultDir}/cr_otus/${infileBase}_otu_table.txt | sed '/#/d' > ${resultDir}/cr_otus/${infileBase}_otu_observations.txt Step 8: Create a phylogenetic tree by pruning GreenGenes and keeping observed otus ${python} ${qiimeDir}/bin/filter_tree.py -i ${qiimeDir}/gg_13_8_otus/trees/97_otus.tree -t ${resultDir}/cr_otus/${infileBase}_otu_observations.txt -o ${resultDir}/cr_otus/${infileBase}_pruned.tree

https://github.com/ProteinsWebTeam/ebi-metagenomics-cwl.git

Path: workflows/qiime-workflow.cwl

Branch/Commit ID: 708fd97
workflow graph rRNA_selection.cwl

https://github.com/proteinswebteam/ebi-metagenomics-cwl.git

Path: tools/rRNA_selection.cwl

Branch/Commit ID: caea457
workflow graph CODEX analysis pipeline using Cytokit

https://github.com/hubmapconsortium/codex-pipeline.git

Path: steps/ometiff_second_stitching.cwl

Branch/Commit ID: b23af94
workflow graph chksum_xam_to_interleaved_fq.cwl

https://github.com/cancerit/workflow-seq-import.git

Path: cwls/chksum_xam_to_interleaved_fq.cwl

Branch/Commit ID: 0.5.0_test
workflow graph Detect Variants workflow for WGS pipeline

https://github.com/apaul7/cancer-genomics-workflow.git

Path: definitions/pipelines/detect_variants_wgs.cwl

Branch/Commit ID: low-vaf
workflow graph fail-wf.cwl

Run failtool which will fail

 https://github.com/Duke-GCB/calrissian.git

Path: input-data/fail-wf.cwl

Branch/Commit ID: master