Explore Workflows

https://github.com/lanl/BEE.git

Path: examples/cat-grep-tar/workflow.cwl

Branch/Commit ID: 17da9ca498f98c0279bc53d25c09210ab256024d

\" The process of updating the GFF format file from identifying TSS - transcription start sites - from paired-end CAGE-seq data. This workflow consists of the following files: (1) Tools/06_combined_exec_TSSr.cwl, (2) Tools/07_join_all_assignedClusters.cwl, (3) Tools/08_uniq_tss_feature.cwl, (4) Tools/09_update_gtf.cwl \"

https://github.com/RyoNozu/CWL4IncorporateTSSintoGXF.git

Path: workflow/04_tssr_subworkflow_pe.cwl

Branch/Commit ID: 9728a86f7b73f7657a1f261e77a14ca59bdd561b

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

Path: bacterial_orthology/wf_bacterial_orthology.cwl

Branch/Commit ID: 54c5074587af001a44eccb4762a4cb25fa24cb3e

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

Path: task_types/tt_cluster_and_qdump.cwl

Branch/Commit ID: c6e7e18969c761803c38762ad6ee91b0001c52e2

The original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **ChIP-Seq** basic analysis workflow for a **paired-end** experiment with Trim Galore. _Trim Galore_ is a wrapper around [Cutadapt](https://github.com/marcelm/cutadapt) and [FastQC](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) to consistently apply adapter and quality trimming to FastQ files, with extra functionality for RRBS data. A [FASTQ](http://maq.sourceforge.net/fastq.shtml) input file has to be provided. In outputs it returns coordinate sorted BAM file alongside with index BAI file, quality statistics for both the input FASTQ files, reads coverage in a form of BigWig file, peaks calling data in a form of narrowPeak or broadPeak files, islands with the assigned nearest genes and region type, data for average tag density plot (on the base of BAM file). Workflow starts with running fastx_quality_stats (steps fastx_quality_stats_upstream and fastx_quality_stats_downstream) from FASTX-Toolkit to calculate quality statistics for both upstream and downstream input FASTQ files. At the same time Bowtie is used to align reads from input FASTQ files to reference genome (Step bowtie_aligner). The output of this step is unsorted SAM file which is being sorted and indexed by samtools sort and samtools index (Step samtools_sort_index). Depending on workflow’s input parameters indexed and sorted BAM file could be processed by samtools rmdup (Step samtools_rmdup) to remove all possible read duplicates. In a case when removing duplicates is not necessary the step returns original input BAM and BAI files without any processing. If the duplicates were removed the following step (Step samtools_sort_index_after_rmdup) reruns samtools sort and samtools index with BAM and BAI files, if not - the step returns original unchanged input files. Right after that macs2 callpeak performs peak calling (Step macs2_callpeak). On the base of returned outputs the next step (Step macs2_island_count) calculates the number of islands and estimated fragment size. If the last one is less that 80 (hardcoded in a workflow) macs2 callpeak is rerun again with forced fixed fragment size value (Step macs2_callpeak_forced). If at the very beginning it was set in workflow input parameters to force run peak calling with fixed fragment size, this step is skipped and the original peak calling results are saved. In the next step workflow again calculates the number of islands and estimated fragment size (Step macs2_island_count_forced) for the data obtained from macs2_callpeak_forced step. If the last one was skipped the results from macs2_island_count_forced step are equal to the ones obtained from macs2_island_count step. Next step (Step macs2_stat) is used to define which of the islands and estimated fragment size should be used in workflow output: either from macs2_island_count step or from macs2_island_count_forced step. If input trigger of this step is set to True it means that macs2_callpeak_forced step was run and it returned different from macs2_callpeak step results, so macs2_stat step should return [fragments_new, fragments_old, islands_new], if trigger is False the step returns [fragments_old, fragments_old, islands_old], where sufix \"old\" defines results obtained from macs2_island_count step and sufix \"new\" - from macs2_island_count_forced step. The following two steps (Step bamtools_stats and bam_to_bigwig) are used to calculate coverage on the base of input BAM file and save it in BigWig format. For that purpose bamtools stats returns the number of mapped reads number which is then used as scaling factor by bedtools genomecov when it performs coverage calculation and saves it in BED format. The last one is then being sorted and converted to BigWig format by bedGraphToBigWig tool from UCSC utilities. Step get_stat is used to return a text file with statistics in a form of [TOTAL, ALIGNED, SUPRESSED, USED] reads count. Step island_intersect assigns genes and regions to the islands obtained from macs2_callpeak_forced. Step average_tag_density is used to calculate data for average tag density plot on the base of BAM file.

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

Path: workflows/trim-chipseq-pe.cwl

Branch/Commit ID: 3fc68366adb179927af5528c27b153abaf94494d

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

Path: v1.0/v1.0/scatter-wf1.cwl

Branch/Commit ID: 17695244222b0301b37cb749fe4a8d89622cd1ad

https://github.com/h3abionet/h3abionet16S.git

Path: workflows-cwl/completeWorkflow.cwl

Branch/Commit ID: b963681265d9de273a50b5f1ffbb54bf8d1fbdd3

Principal Component Analysis --------------- Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables (entities each of which takes on various numerical values) into a set of values of linearly uncorrelated variables called principal components. The calculation is done by a singular value decomposition of the (centered and possibly scaled) data matrix, not by using eigen on the covariance matrix. This is generally the preferred method for numerical accuracy.

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

Path: workflows/pca.cwl

Branch/Commit ID: 7eef0294395d83ff0765fce61726a59d71126422

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

Path: testdata/step-valuefrom3-wf_v1_2.cwl

Branch/Commit ID: 0ad6983898f0d9001fe0f416f97c4d8b940e384a

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

Path: cwltool/schemas/v1.0/v1.0/scatter-wf2.cwl

Branch/Commit ID: 203797516329f7fb8aa5e763e6f9b331c63c3060