Explore Workflows
View already parsed workflows here or click here to add your own
| Graph | Name | Retrieved From | View |
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cluster_blastp_wnode and gpx_qdump combined
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https://github.com/ncbi/pgap.git
Path: task_types/tt_cluster_and_qdump.cwl Branch/Commit ID: 09774c78a965dd8f6c315597a53eef5998a3c1b6 |
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Subworkflow to allow calling different SV callers which require bam files as inputs
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https://github.com/genome/analysis-workflows.git
Path: definitions/subworkflows/single_sample_sv_callers.cwl Branch/Commit ID: a08de598edc04f340fdbff76c9a92336a7702022 |
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Seurat Cluster
Seurat Cluster ============== Runs filtering, integration, and clustering analyses for Cell Ranger Count Gene Expression or Cell Ranger Aggregate experiments. |
https://github.com/datirium/workflows.git
Path: workflows/seurat-cluster.cwl Branch/Commit ID: e45ab1b9ac5c9b99fdf7b3b1be396dc42c2c9620 |
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trnascan_wnode and gpx_qdump combined
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https://github.com/ncbi/pgap.git
Path: bacterial_trna/wf_scan_and_dump.cwl Branch/Commit ID: 609aead9804a8f31fa9b3dbc7e52105aec487f31 |
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tt_kmer_compare_wnode
Pairwise comparison |
https://github.com/ncbi/pgap.git
Path: task_types/tt_kmer_compare_wnode.cwl Branch/Commit ID: 09774c78a965dd8f6c315597a53eef5998a3c1b6 |
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kmer_top_n_extract
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https://github.com/ncbi/pgap.git
Path: task_types/tt_kmer_top_n_extract.cwl Branch/Commit ID: d218e081d8f6a4fdab56a38ce0fc2fae6216cecc |
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taxonomy_check_16S
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https://github.com/ncbi/pgap.git
Path: task_types/tt_taxonomy_check_16S.cwl Branch/Commit ID: 609aead9804a8f31fa9b3dbc7e52105aec487f31 |
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kmer_ref_compare_wnode
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https://github.com/ncbi/pgap.git
Path: task_types/tt_kmer_ref_compare_wnode.cwl Branch/Commit ID: 09774c78a965dd8f6c315597a53eef5998a3c1b6 |
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GAT - Genomic Association Tester
GAT: Genomic Association Tester ============================================== A common question in genomic analysis is whether two sets of genomic intervals overlap significantly. This question arises, for example, in the interpretation of ChIP-Seq or RNA-Seq data. The Genomic Association Tester (GAT) is a tool for computing the significance of overlap between multiple sets of genomic intervals. GAT estimates significance based on simulation. Gat implemements a sampling algorithm. Given a chromosome (workspace) and segments of interest, for example from a ChIP-Seq experiment, gat creates randomized version of the segments of interest falling into the workspace. These sampled segments are then compared to existing genomic annotations. The sampling method is conceptually simple. Randomized samples of the segments of interest are created in a two-step procedure. Firstly, a segment size is selected from to same size distribution as the original segments of interest. Secondly, a random position is assigned to the segment. The sampling stops when exactly the same number of nucleotides have been sampled. To improve the speed of sampling, segment overlap is not resolved until the very end of the sampling procedure. Conflicts are then resolved by randomly removing and re-sampling segments until a covering set has been achieved. Because the size of randomized segments is derived from the observed segment size distribution of the segments of interest, the actual segment sizes in the sampled segments are usually not exactly identical to the ones in the segments of interest. This is in contrast to a sampling method that permutes segment positions within the workspace. |
https://github.com/datirium/workflows.git
Path: workflows/gat-run.cwl Branch/Commit ID: 8049a781ac4aae579fbd3036fa0bf654532f15be |
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kmer_seq_entry_extract_wnode
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https://github.com/ncbi/pgap.git
Path: task_types/tt_kmer_seq_entry_extract_wnode.cwl Branch/Commit ID: 09774c78a965dd8f6c315597a53eef5998a3c1b6 |
