Explore Workflows
View already parsed workflows here or click here to add your own
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transcriptome_assemble.cwl
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Path: workflow/transcriptome_assemble/transcriptome_assemble.cwl Branch/Commit ID: 4c90bc270e271b24caacaf000116727ff8ec81f8 |
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sec-wf.cwl
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Path: tests/wf/sec-wf.cwl Branch/Commit ID: 814bd0405a7701efc7d63e8f0179df394c7766f7 |
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Bacterial Annotation, pass 3, structural annotation, functional annotation: ab initio GeneMark, by WP, by HMM (second pass)
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Path: bacterial_annot/wf_bacterial_annot_pass3.cwl Branch/Commit ID: f225cd99b0e0a5043dd102f8b33a6139fefe9ea4 |
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Super-enhancer post ChIP-Seq analysis
Super-enhancers, consist of clusters of enhancers that are densely occupied by the master regulators and Mediator. Super-enhancers differ from typical enhancers in size, transcription factor density and content, ability to activate transcription, and sensitivity to perturbation. Use to create stitched enhancers, and to separate super-enhancers from typical enhancers using sequencing data (.bam) given a file of previously identified constituent enhancers (.gff) |
Path: workflows/super-enhancer.cwl Branch/Commit ID: 5e7385b8cfa4ddae822fff37b6bd22eb0370b389 |
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mutect parallel workflow
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Path: definitions/subworkflows/mutect.cwl Branch/Commit ID: eb0092603bf57acb7bda08a06e4f2f1e2a8c9b6d |
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kmer_ref_compare_wnode
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Path: task_types/tt_kmer_ref_compare_wnode.cwl Branch/Commit ID: 0514ffe248dd11068a3f2268bc67b6ce5ab051d2 |
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BLAST against rRNA db
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Path: bacterial_noncoding/wf_blastn.cwl Branch/Commit ID: f225cd99b0e0a5043dd102f8b33a6139fefe9ea4 |
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Add snv and indel bam-readcount files to a vcf
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Path: definitions/subworkflows/vcf_readcount_annotator.cwl Branch/Commit ID: eb0092603bf57acb7bda08a06e4f2f1e2a8c9b6d |
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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 |
Path: workflows/qiime-workflow.cwl Branch/Commit ID: 8e196ab4fc4e06d97a3d943d6bc59b4e970ed129 |
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BLAST against rRNA db
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Path: bacterial_noncoding/wf_blastn.cwl Branch/Commit ID: 4f4448f71645275db5b84eb551990dfe3bf37cbb |
