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Graph Name Retrieved From View
workflow graph inpdir_update_wf.cwl

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

Path: tests/inpdir_update_wf.cwl

Branch/Commit ID: 3e90671b25f7840ef2926ad2bacbf447772dda94
workflow graph count-lines15-wf.cwl

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

Path: tests/count-lines15-wf.cwl

Branch/Commit ID: 7d7986a6e852ca6e3239c96d3a05dd536c76c903
workflow graph diadem_workflow.cwl

https://github.com/cnherrera/CWL_Workflow_DIADEM_use_case.git

Path: diadem_workflow.cwl

Branch/Commit ID: 5a791a54d7e3f9e449235396c4815fd74cc45e72
workflow graph diadem_workflow.cwl

https://github.com/cnherrera/Workflow_DIADEM_use_case.git

Path: diadem_workflow.cwl

Branch/Commit ID: 99222a8f035d2f9405f7dc8e9134c7469d9a5830
workflow graph diadem_workflow.cwl

https://github.com/cnherrera/CWL_DIADEM_use_case.git

Path: diadem_workflow.cwl

Branch/Commit ID: 13471fcd33e9e1a05d92056c3acca91797f76cf2
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: 7d7986a6e852ca6e3239c96d3a05dd536c76c903
workflow graph iwdr_with_nested_dirs.cwl

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

Path: tests/iwdr_with_nested_dirs.cwl

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

https://github.com/cnherrera/testCWL.git

Path: diadem_workflow.cwl

Branch/Commit ID: cea79cd8ef6868b7b27be2e66c82f7140f92d853
workflow graph 16S metagenomic paired-end QIIME2 Sample (preprocessing)

A workflow for processing a single 16S sample via a QIIME2 pipeline. ## __Outputs__ #### Output files: - overview.md, list of inputs - demux.qzv, summary visualizations of imported data - alpha-rarefaction.qzv, plot of OTU rarefaction - taxa-bar-plots.qzv, relative frequency of taxomonies barplot ## __Inputs__ #### General Info - Sample short name/Alias: Used for samplename in downstream analyses. Ensure this is the same name used in the metadata samplesheet. - Environment: where the sample was collected - Catalog No.: catalog number if available (optional) - Read 1 FASTQ file: Read 1 FASTQ file from a paired-end sequencing run. - Read 2 FASTQ file: Read 2 FASTQ file that pairs with the input R1 file. - Trim 5' of R1: Recommended if adapters are still on the input sequences. Trims the first J bases from the 5' end of each forward read. - Trim 5' of R2: Recommended if adapters are still on the input sequences. Trims the first K bases from the 5' end of each reverse read. - Truncate 3' of R1: Recommended if quality drops off along the length of the read. Clips the forward read starting M bases from the 5' end (before trimming). - Truncate 3' of R2: Recommended if quality drops off along the length of the read. Clips the reverse read starting N bases from the 5' end (before trimming). - Threads: Number of threads to use for steps that support multithreading. ### __Data Analysis Steps__ 1. Generate FASTX quality statistics for visualization of unmapped, raw FASTQ reads. 2. Import the data, make a qiime artifact (demux.qza), and summary visualization 3. Denoising will detect and correct (where possible) Illumina amplicon sequence data. This process will additionally filter any phiX reads (commonly present in marker gene Illumina sequence data) that are identified in the sequencing data, and will filter chimeric sequences. 4. Generate a phylogenetic tree for diversity analyses and rarefaction processing and plotting. 5. Taxonomy classification of amplicons. Performed using a Naive Bayes classifier trained on the Greengenes2 database \"gg_2022_10_backbone_full_length.nb.qza\". ### __References__ 1. Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, Alexander H, Alm EJ, Arumugam M, Asnicar F, Bai Y, Bisanz JE, Bittinger K, Brejnrod A, Brislawn CJ, Brown CT, Callahan BJ, Caraballo-Rodríguez AM, Chase J, Cope EK, Da Silva R, Diener C, Dorrestein PC, Douglas GM, Durall DM, Duvallet C, Edwardson CF, Ernst M, Estaki M, Fouquier J, Gauglitz JM, Gibbons SM, Gibson DL, Gonzalez A, Gorlick K, Guo J, Hillmann B, Holmes S, Holste H, Huttenhower C, Huttley GA, Janssen S, Jarmusch AK, Jiang L, Kaehler BD, Kang KB, Keefe CR, Keim P, Kelley ST, Knights D, Koester I, Kosciolek T, Kreps J, Langille MGI, Lee J, Ley R, Liu YX, Loftfield E, Lozupone C, Maher M, Marotz C, Martin BD, McDonald D, McIver LJ, Melnik AV, Metcalf JL, Morgan SC, Morton JT, Naimey AT, Navas-Molina JA, Nothias LF, Orchanian SB, Pearson T, Peoples SL, Petras D, Preuss ML, Pruesse E, Rasmussen LB, Rivers A, Robeson MS, Rosenthal P, Segata N, Shaffer M, Shiffer A, Sinha R, Song SJ, Spear JR, Swafford AD, Thompson LR, Torres PJ, Trinh P, Tripathi A, Turnbaugh PJ, Ul-Hasan S, van der Hooft JJJ, Vargas F, Vázquez-Baeza Y, Vogtmann E, von Hippel M, Walters W, Wan Y, Wang M, Warren J, Weber KC, Williamson CHD, Willis AD, Xu ZZ, Zaneveld JR, Zhang Y, Zhu Q, Knight R, and Caporaso JG. 2019. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nature Biotechnology 37: 852–857. https://doi.org/10.1038/s41587-019-0209-9

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

Path: workflows/qiime2-sample-pe.cwl

Branch/Commit ID: fa4f172486288a1a9d23864f1d6962d85a453e16
workflow graph taxcheck.cwl

Perform taxonomic identification tasks on an input genome

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

Path: taxcheck.cwl

Branch/Commit ID: 1cfd46014be8d867044cb10d1ddde0cb3068ee84