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Graph Name Retrieved From View
workflow graph gathered exome alignment and somatic variant detection for cle purpose

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

Path: definitions/pipelines/gathered_cle_somatic_exome.cwl

Branch/Commit ID: 1560e7817fdb71d58aca7f98aba68809d840ade1
workflow graph CLIP-Seq pipeline for single-read experiment NNNNG

Cross-Linking ImmunoPrecipitation ================================= `CLIP` (`cross-linking immunoprecipitation`) is a method used in molecular biology that combines UV cross-linking with immunoprecipitation in order to analyse protein interactions with RNA or to precisely locate RNA modifications (e.g. m6A). (Uhl|Houwaart|Corrado|Wright|Backofen|2017)(Ule|Jensen|Ruggiu|Mele|2003)(Sugimoto|König|Hussain|Zupan|2012)(Zhang|Darnell|2011) (Ke| Alemu| Mertens| Gantman|2015) CLIP-based techniques can be used to map RNA binding protein binding sites or RNA modification sites (Ke| Alemu| Mertens| Gantman|2015)(Ke| Pandya-Jones| Saito| Fak|2017) of interest on a genome-wide scale, thereby increasing the understanding of post-transcriptional regulatory networks. The identification of sites where RNA-binding proteins (RNABPs) interact with target RNAs opens the door to understanding the vast complexity of RNA regulation. UV cross-linking and immunoprecipitation (CLIP) is a transformative technology in which RNAs purified from _in vivo_ cross-linked RNA-protein complexes are sequenced to reveal footprints of RNABP:RNA contacts. CLIP combined with high-throughput sequencing (HITS-CLIP) is a generalizable strategy to produce transcriptome-wide maps of RNA binding with higher accuracy and resolution than standard RNA immunoprecipitation (RIP) profiling or purely computational approaches. The application of CLIP to Argonaute proteins has expanded the utility of this approach to mapping binding sites for microRNAs and other small regulatory RNAs. Finally, recent advances in data analysis take advantage of cross-link–induced mutation sites (CIMS) to refine RNA-binding maps to single-nucleotide resolution. Once IP conditions are established, HITS-CLIP takes ~8 d to prepare RNA for sequencing. Established pipelines for data analysis, including those for CIMS, take 3–4 d. Workflow -------- CLIP begins with the in-vivo cross-linking of RNA-protein complexes using ultraviolet light (UV). Upon UV exposure, covalent bonds are formed between proteins and nucleic acids that are in close proximity. (Darnell|2012) The cross-linked cells are then lysed, and the protein of interest is isolated via immunoprecipitation. In order to allow for sequence specific priming of reverse transcription, RNA adapters are ligated to the 3' ends, while radiolabeled phosphates are transferred to the 5' ends of the RNA fragments. The RNA-protein complexes are then separated from free RNA using gel electrophoresis and membrane transfer. Proteinase K digestion is then performed in order to remove protein from the RNA-protein complexes. This step leaves a peptide at the cross-link site, allowing for the identification of the cross-linked nucleotide. (König| McGlincy| Ule|2012) After ligating RNA linkers to the RNA 5' ends, cDNA is synthesized via RT-PCR. High-throughput sequencing is then used to generate reads containing distinct barcodes that identify the last cDNA nucleotide. Interaction sites can be identified by mapping the reads back to the transcriptome.

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

Path: workflows/clipseq-se.cwl

Branch/Commit ID: e238d1756f1db35571e84d72e1699e5d1540f10c
workflow graph cluster_blastp_wnode and gpx_qdump combined

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

Path: task_types/tt_cluster_and_qdump.cwl

Branch/Commit ID: 9abcceb95c8dcb74b98d7eeda265d8f3a9a4329e
workflow graph Subworkflow that runs cnvkit in single sample mode and returns a vcf file

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

Path: definitions/subworkflows/cnvkit_single_sample.cwl

Branch/Commit ID: d57c2af01a3cb6016e5a264f60641eafd2e5aa05
workflow graph output-arrays-file-wf.cwl

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

Path: tests/output-arrays-file-wf.cwl

Branch/Commit ID: 0e37d46e793e72b7c16b5ec03e22cb3ce1f55ba3
workflow graph filtering.cwl

https://github.com/mskcc/ACCESS-Pipeline.git

Path: workflows/subworkflows/filtering.cwl

Branch/Commit ID: b0f226a9ac5152f3afe0d38c8cd54aa25b8b01cf
workflow graph Single-cell RNA-Seq Analyze

Single-cell RNA-Seq Analyze Runs filtering, normalization, scaling, integration (optionally) and clustering for a single or aggregated single-cell RNA-Seq datasets.

 https://github.com/Barski-lab/sc-seq-analysis.git

Path: workflows/sc-rna-analyze-wf.cwl

Branch/Commit ID: 8614e5d20f5e81dce537216bd340cdbc1067bbc7
workflow graph allele-alignreads-se-pe.cwl

Workflow maps FASTQ files from `fastq_files` input into reference genome `reference_star_indices_folder` and insilico generated `insilico_star_indices_folder` genome (concatenated genome for both `strain1` and `strain2` strains). For both genomes STAR is run with `outFilterMultimapNmax` parameter set to 1 to discard all of the multimapped reads. For insilico genome SAM file is generated. Then it's splitted into two SAM files based on strain names and then sorted by coordinates into the BAM format. For reference genome output BAM file from STAR slignment is also coordinate sorted.

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

Path: subworkflows/allele-alignreads-se-pe.cwl

Branch/Commit ID: 62323c137c0ce9b3f843df0dfbda28dafa7c90cf
workflow graph kmer_cache_retrieve

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

Path: task_types/tt_kmer_cache_retrieve.cwl

Branch/Commit ID: be465ad19b07378f3f863f2c4e0019b420c859f2
workflow graph nestedworkflows.cwl

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

Path: cwltool/schemas/v1.0/examples/nestedworkflows.cwl

Branch/Commit ID: 46b7f9766d1bc8a4871474eee25ec730b4e173da