Explore Workflows

Quality Control (raw data), Raw Data trimming and Quality Control (pre-processed)

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

Path: structuralvariants/cwl/abstract_operations/subworkflows/trimmed_fastq.cwl

Branch/Commit ID: 26ae4914651d5b3e188028d1e9d88a391b3f6730

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

Path: task_types/tt_format_rrnas_from_seq_entry.cwl

Branch/Commit ID: 686b570a9fa46f3ace3f8e9935490b75df86a1fc

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

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

Branch/Commit ID: 227f35a5ed50c423afba2353871950aa61d58872

This workflow clean up vectros from fastq files

https://github.com/ncbi/cwl-ngs-workflows-cbb.git

Path: workflows/File-formats/remove-fastq-reads-from-blast.cwl

Branch/Commit ID: f9447c1ac522e17531097c93a169a1a31453e874

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

Path: src/test/resources/cwl/lobstr-v1/lobSTR-workflow.cwl

Branch/Commit ID: 9f0d580e8037ff41bd9968fc0e8a9d65f9f3f035

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

Path: definitions/subworkflows/duplex_alignment.cwl

Branch/Commit ID: 788bdc99c1d5b6ee7c431c3c011eb30d385c1370

https://github.com/adamscharlotte/CWL-workflow.git

Path: Protein_Inference_workflow_challenge.cwl

Branch/Commit ID: f165c14d6d2e20a5133fc42251ae565fcbe520f6

What is MAnorm? -------------- MAnorm is a robust model for quantitative comparison of ChIP-Seq data sets of TFs (transcription factors) or epigenetic modifications and you can use it for: * Normalization of two ChIP-seq samples * Quantitative comparison (differential analysis) of two ChIP-seq samples * Evaluating the overlap enrichment of the protein binding sites(peaks) * Elucidating underlying mechanisms of cell-type specific gene regulation How MAnorm works? ---------------- MAnorm uses common peaks of two samples as a reference to build the rescaling model for normalization, which is based on the empirical assumption that if a chromatin-associated protein has a substantial number of peaks shared in two conditions, the binding at these common regions will tend to be determined by similar mechanisms, and thus should exhibit similar global binding intensities across samples. The observed differences on common peaks are presumed to reflect the scaling relationship of ChIP-Seq signals between two samples, which can be applied to all peaks. What do the inputs mean? ---------------- ### General **Experiment short name/Alias** * short name for you experiment to identify among the others **ChIP-Seq PE sample 1** * previously analyzed ChIP-Seq paired-end experiment to be used as Sample 1 **ChIP-Seq PE sample 2** * previously analyzed ChIP-Seq paired-end experiment to be used as Sample 2 **Genome** * Reference genome to be used for gene assigning ### Advanced **Reads shift size for sample 1** * This value is used to shift reads towards 3' direction to determine the precise binding site. Set as half of the fragment length. Default 100 **Reads shift size for sample 2** * This value is used to shift reads towards 5' direction to determine the precise binding site. Set as half of the fragment length. Default 100 **M-value (log2-ratio) cutoff** * Absolute M-value (log2-ratio) cutoff to define biased (differential binding) peaks. Default: 1.0 **P-value cutoff** * P-value cutoff to define biased peaks. Default: 0.01 **Window size** * Window size to count reads and calculate read densities. 2000 is recommended for sharp histone marks like H3K4me3 and H3K27ac, and 1000 for TFs or DNase-seq. Default: 2000

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

Path: workflows/manorm-pe.cwl

Branch/Commit ID: 480e99a4bb3046e0565113d9dca294e0895d3b0c

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

Path: task_types/tt_bact_get_kmer_reference.cwl

Branch/Commit ID: 17bae57a1f00f5c6db8f3a82d86262f12b8153cf

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

Path: task_types/tt_cluster_and_qdump.cwl

Branch/Commit ID: 5e92165ac2c11608ab2db42fe2d66eabe72dbb40