Explore Workflows

What is THOR? -------------- THOR is an HMM-based approach to detect and analyze differential peaks in two sets of ChIP-seq data from distinct biological conditions with replicates. THOR performs genomic signal processing, peak calling and p-value calculation in an integrated framework. For more information please refer to: ------------------------------------- Allhoff, M., Sere K., Freitas, J., Zenke, M., Costa, I.G. (2016), Differential Peak Calling of ChIP-seq Signals with Replicates with THOR, Nucleic Acids Research, epub gkw680.

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

Path: workflows/rgt-thor.cwl

Branch/Commit ID: 935a78f1aff757f977de4e3672aefead3b23606b

Single-cell Differential Expression =================================== Runs differential expression analysis for a subset of cells between two selected conditions.

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

Path: workflows/sc_diff_expr.cwl

Branch/Commit ID: 1a46cb0e8f973481fe5ae3ae6188a41622c8532e

Workflow runs homer-make-tag-directory.cwl tool using scatter for the following inputs - bam_file - fragment_size - total_reads `dotproduct` is used as a `scatterMethod`, so one element will be taken from each array to construct each job: 1) bam_file[0] fragment_size[0] total_reads[0] 2) bam_file[1] fragment_size[1] total_reads[1] ... N) bam_file[N] fragment_size[N] total_reads[N] `bam_file`, `fragment_size` and `total_reads` arrays should have the identical order.

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

Path: tools/heatmap-prepare.cwl

Branch/Commit ID: 1a46cb0e8f973481fe5ae3ae6188a41622c8532e

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

Path: task_types/tt_bact_get_kmer_reference.cwl

Branch/Commit ID: 5282690e0f634a5f83107ba878fe62cbbb347408

ChIP-seq 01 QC - reads: PE

https://github.com/Duke-GCB/GGR-cwl.git

Path: v1.0/ChIP-seq_pipeline/01-qc-pe.cwl

Branch/Commit ID: 6da8cef69f3a585fc3e2f4f2f730d361cbe2e978

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

Path: task_types/tt_taxonomy_check_16S.cwl

Branch/Commit ID: 1b8d71c75156a1a62bf0477d59db26010e2dcc29

Runs ChIP-Seq BioWardrobe basic analysis with single-end data file.

https://github.com/Barski-lab/workflows.git

Path: workflows/chipseq-se.cwl

Branch/Commit ID: 12edfc2207507e53c6b5bb21e50decb5535a12f7

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

Path: subworkflows/chipseq-gen-bigwig.cwl

Branch/Commit ID: 58d8b329a6531237205cc36d70604ab0be064402

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 should be used only with the single-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 1 (after running STAR) 5. Generate BigWig file on the base of 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: 564156a9e1cc7c3679a926c479ba3ae133b1bfd4

Workflow runs group-isoforms.cwl tool using scatter for isoforms_file input. genes_filename and common_tss_filename inputs are ignored.

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

Path: tools/group-isoforms-batch.cwl

Branch/Commit ID: 8049a781ac4aae579fbd3036fa0bf654532f15be