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Graph Name Retrieved From View
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: 7eef0294395d83ff0765fce61726a59d71126422

workflow graph Detect Variants workflow for WGS pipeline

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

Path: definitions/pipelines/detect_variants_wgs.cwl

Branch/Commit ID: d3e4bf55753cd92f97537c7d701187ea92d1e5f0

workflow graph tt_kmer_compare_wnode

Pairwise comparison

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

Path: task_types/tt_kmer_compare_wnode.cwl

Branch/Commit ID: 2afb5ebafd1353ba063cc74ee9a7eaf347afce5c

workflow graph kmer_top_n_extract

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

Path: task_types/tt_kmer_top_n_extract.cwl

Branch/Commit ID: 192b813eed8c0d368e69057cb39415175dd15128

workflow graph scatter-wf2_v1_2.cwl

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

Path: testdata/scatter-wf2_v1_2.cwl

Branch/Commit ID: c1875d54dedc41b1d2fa08634dcf1caa8f1bc631

workflow graph step-valuefrom3-wf_v1_0.cwl

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

Path: testdata/step-valuefrom3-wf_v1_0.cwl

Branch/Commit ID: c1875d54dedc41b1d2fa08634dcf1caa8f1bc631

workflow graph cond-wf-003.cwl

https://github.com/common-workflow-language/cwl-v1.2.git

Path: tests/conditionals/cond-wf-003.cwl

Branch/Commit ID: e62f99dd79d6cb9c157cceb458f74200da84f6e9

workflow graph cond-wf-010.cwl

https://github.com/common-workflow-language/cwl-v1.2.git

Path: tests/conditionals/cond-wf-010.cwl

Branch/Commit ID: e62f99dd79d6cb9c157cceb458f74200da84f6e9

workflow graph hmmsearch_wnode and gpx_qdump combined workflow to apply scatter/gather

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

Path: task_types/tt_hmmsearch_wnode_plus_qdump.cwl

Branch/Commit ID: e0fb04a0d8bc648183c6b71d099ce7aea3c3b3ff

workflow graph step-valuefrom2-wf_v1_0.cwl

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

Path: testdata/step-valuefrom2-wf_v1_0.cwl

Branch/Commit ID: c1875d54dedc41b1d2fa08634dcf1caa8f1bc631