Explore Workflows

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: 69643d8c15f5357a320aa7e2f6adb2e71302fd20

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

Path: testdata/count-lines7-single-source-wf_v1_2.cwl

Branch/Commit ID: 5759b4275906e6cfe13912c8426de2a2237cb4b0

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

Path: testdata/step-valuefrom3-wf_v1_0.cwl

Branch/Commit ID: 5759b4275906e6cfe13912c8426de2a2237cb4b0

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

Path: tests/wf/conflict.cwl

Branch/Commit ID: 1b5633876aabd4cb57ef3f1fe91c853f3ee82e46

Packed ID: main

The original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for a **pair-end** experiment. A corresponded input [FASTQ](http://maq.sourceforge.net/fastq.shtml) file has to be provided. Current workflow must be used with paired-end RNA-Seq data. It performs the following steps: 1. Trim adapters from input FASTQ files 2. Use STAR to align reads from input FASTQ files according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 3. Use fastx_quality_stats to analyze input FASTQ files and generate quality statistics files 4. Use samtools sort to generate coordinate sorted BAM(+BAI) file pair from the unsorted BAM file obtained on the step 2 (after running STAR) 5. Generate BigWig file using sorted BAM file 6. Map input FASTQ files 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/trim-rnaseq-pe.cwl

Branch/Commit ID: 69643d8c15f5357a320aa7e2f6adb2e71302fd20

https://github.com/ResearchObject/runcrate.git

Path: cwl/multisource/wf.cwl

Branch/Commit ID: 376f6b2c6332a4742d4512d6e1fb785a2f8b7285

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

Path: testdata/count-lines7-wf_v1_1.cwl

Branch/Commit ID: 5759b4275906e6cfe13912c8426de2a2237cb4b0

Animation of an oil spill with openoil

https://github.com/ILIAD-ocean-twin/application_package.git

Path: openoil/pipeline_v2.cwl

Branch/Commit ID: 2f678aa688683e20169abaaec9166b4a32403523

Packed ID: openoil_pipeline

Single-Cell ATAC-Seq Genome Coverage Generates genome coverage tracks from chromatin accessibility data of selected cells

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

Path: workflows/sc-atac-coverage.cwl

Branch/Commit ID: 69643d8c15f5357a320aa7e2f6adb2e71302fd20

https://github.com/mskcc/argos-cwl.git

Path: modules/pair/alignment-pair.cwl

Branch/Commit ID: 0b9721d7d512352c7f80b27f42b3192a585ed5f6