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Graph Name Retrieved From View
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: 8e196ab
workflow graph SetArrayElementCoordinates

Transform array element coordinates into the coordinate system required by the simulation pipeline (i.e., CORSIKA system).

 https://github.com/gammasim/workflows.git

Path: workflows/SetArrayElementCoordinates.cwl

Branch/Commit ID: main
workflow graph Apply filters to VCF file

https://github.com/ChrisMaherLab/PACT.git

Path: subworkflows/filter_vcf.cwl

Branch/Commit ID: master
workflow graph scRNA-seq pipeline using Salmon and Alevin

https://github.com/hubmapconsortium/salmon-rnaseq.git

Path: pipeline.cwl

Branch/Commit ID: 6591870
workflow graph QIIME2 Step 2 (DADA2 option)

QIIME2 DADA2, feature summaries, phylogenetic diversity tree, taxonomic analysis and ancom

https://github.com/bespin-workflows/16s-qiime2.git

Path: 16s-step2-dada2-paired.cwl

Branch/Commit ID: develop
workflow graph steps.cwl

https://github.com/dimitrapanou/scrnaseq-cwl.git

Path: steps.cwl

Branch/Commit ID: master
workflow graph cmsearch-multimodel.cwl

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

Path: workflows/cmsearch-multimodel.cwl

Branch/Commit ID: 930a2cf
workflow graph Optical throughput measurements via muon ring analysis

Upon receiving a new DL0 data product (from either Monte Carlo simulations or observations), DPPS triggers the CalibPipe (ctapipe-process) to process the data using ctapipe, extracting the signal charges and reconstructing muon parameters. The second step involves using the CalibPipe tool to estimate the telescope’s optical throughput using a predefined number of muon events.

https://github.com/burmist-git/076_cwl.git

Path: uc-optical-throughput-calibration-with-muons.cwl

Branch/Commit ID: master
workflow graph CNV_pipeline

https://gitlab.bsc.es/lrodrig1/structuralvariants_poc.git

Path: structuralvariants/cwl/abstract_workflow/abstract_workflow.cwl

Branch/Commit ID: master
workflow graph Run tRNAScan

https://github.com/ncbi/pgap.git

Path: bacterial_trna/wf_trnascan.cwl

Branch/Commit ID: master