Explore Workflows

https://github.com/common-workflow-language/cwl-utils.git

Path: testdata/workflow_input_sf_expr_array_v1_2.cwl

Branch/Commit ID: 8058c7477097f90205dd7d8481781eb3737ea9c9

https://github.com/common-workflow-language/cwl-v1.1.git

Path: tests/record-in-secondaryFiles-missing-wf.cwl

Branch/Commit ID: e515226f8ac0f7985cd94dae4a301150adae3050

https://github.com/common-workflow-language/cwl-v1.2.git

Path: tests/count-lines11-extra-step-wf-noET.cwl

Branch/Commit ID: a5073143db4155e05df8d2e7eb59d9e62acd65a5

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/bisulfite_qc.cwl

Branch/Commit ID: 5cb188131f786ed33156e2f0e3dd63ab9c04245d

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/align_sort_markdup.cwl

Branch/Commit ID: b7d9ace34664d3cedb16f2512c8a6dc6debfc8ca

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 pair-end** 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 the pair-end 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

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

Path: workflows/rnaseq-pe-dutp-mitochondrial.cwl

Branch/Commit ID: ebbf23764ede324cabc064bd50647c1f643726fa

Perform taxonomic identification tasks on an input genome

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

Path: ani.cwl

Branch/Commit ID: 2d54b11cc9891c9aa52515fe4f8cd9cba12c6629

https://github.com/genome/analysis-workflows.git

Path: definitions/pipelines/umi_duplex_alignment.cwl

Branch/Commit ID: d2c2f2eb846ae2e9cdcab46e3bb88e42126cb3f5

Sequence reads are first cleaned from adapters and transformed into fully bisulfite-converted forward (C->T) and reverse read (G->A conversion of the forward strand) versions, before they are aligned to similarly converted versions of the genome (also C->T and G->A converted). Sequence reads that produce a unique best alignment from the four alignment processes against the bisulfite genomes (which are running in parallel) are then compared to the normal genomic sequence and the methylation state of all cytosine positions in the read is inferred. A read is considered to align uniquely if an alignment has a unique best alignment score (as reported by the AS:i field). If a read produces several alignments with the same number of mismatches or with the same alignment score (AS:i field), a read (or a read-pair) is discarded altogether. On the next step we extract the methylation call for every single C analysed. The position of every single C will be written out to a new output file, depending on its context (CpG, CHG or CHH), whereby methylated Cs will be labelled as forward reads (+), non-methylated Cs as reverse reads (-). The output of the methylation extractor is then transformed into a bedGraph and coverage file. The bedGraph counts output is then used to generate a genome-wide cytosine report which reports the number on every single CpG (optionally every single cytosine) in the genome, irrespective of whether it was covered by any reads or not. As this type of report is informative for cytosines on both strands the output may be fairly large (~46mn CpG positions or >1.2bn total cytosine positions in the human genome).

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

Path: workflows/bismark-methylation-se.cwl

Branch/Commit ID: 675a3ff982091faf304931e9261aacdbabf51702

https://github.com/common-workflow-language/cwltool.git

Path: cwltool/schemas/v1.0/v1.0/echo-wf-default.cwl

Branch/Commit ID: b82ce7ae901a54c7a062fd5eefd8d5ceb5a4d684