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Graph Name Retrieved From View
workflow graph fillout_index_prefilter.cwl

https://github.com/mskcc/pluto-cwl.git

Path: cwl/fillout_index_prefilter.cwl

Branch/Commit ID: master
workflow graph docker_VisIVO_ImpFilterView_Workflow_GADGET_PD.cwl

https://github.com/VisIVOLab/VisIVOCWL.git

Path: Workflow_4/docker_VisIVO_ImpFilterView_Workflow_GADGET_PD.cwl

Branch/Commit ID: main
workflow graph Perform camera calibration

Camera calibration data (from telescope-level calibration events) will be recorded alongside science data during and around each observation night by ACADA. Different calibration event types will be recorded to the different streams at this stage. Interleaved flat-field and sky pedestal events are tagged at the telescope level, allowing the data to directly align with the functional decomposition of the CalibPipe and avoid the need of additional event-type filtering. Following this, pixel- and channel-wise camera calibration coefficients are calculated as a function of time. This process includes the computation of aggregated time-series statistics for the calibration events, as well as the detection of non-nominal pixels and time periods (UC-120-2.21). The aggregated statistics are further processed to derive the sky pedestal offsets per waveform sample, flat-fielding coefficients, and pixel timing corrections. Additionally, the CalibPipe calculates the absolute gain for each pixel and gain channel as a function of time. This process will ultimately yield a multiplicative coefficient for the absolute calibration of extracted charge into photoelectrons. To achieve accurate absolute gain and charge calibration, CalibPipe derives telescope-specific systematic corrections (UC-120-2.22) and the conversion factors from digital counts to single photoelectrons (UC-120-2.23).

https://gitlab.cta-observatory.org/cta-computing/dpps/calibrationpipeline/calibpipe.git

Path: workflows/telescope/camera/uc-120-2.20-perform-camera-calibration.cwl

Branch/Commit ID: rc-1.0
workflow graph dedup-2-pass.cwl

run 2-pass dedup: algo LocusCollector + algo Dedup sequentially

 https://github.com/sentieon/sentieon-cwl.git

Path: stage/dedup-2-pass.cwl

Branch/Commit ID: master
workflow graph VIRTUS.PE.cwl

https://github.com/yyoshiaki/VIRTUS.git

Path: workflow/VIRTUS.PE.cwl

Branch/Commit ID: master
workflow graph pcr-bottleneck-coef.cwl

ChIP-seq - map - PCR Bottleneck Coefficients

 https://github.com/alexbarrera/GGR-cwl.git

Path: v1.0/map/pcr-bottleneck-coef.cwl

Branch/Commit ID: master
workflow graph gatk4W-spark.cwl

Author: AMBARISH KUMAR er.ambarish@gmail.com & ambari73_sit@jnu.ac.in This is a proposed standard operating procedure for genomic variant detection using GATK4. It is hoped to be effective and useful for getting SARS-CoV-2 genome variants. It uses Illumina RNASEQ reads and genome sequence.

https://github.com/ambarishK/bio-cwl-tools.git

Path: gatk4W-spark.cwl

Branch/Commit ID: release
workflow graph cond-wf-002.cwl

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

Path: tests/conditionals/cond-wf-002.cwl

Branch/Commit ID: main
workflow graph bam_collapsing.cwl

https://github.com/msk-access/bam_collapsing.git

Path: bam_collapsing.cwl

Branch/Commit ID: master
workflow graph EMG pipeline v3.0 (paired end version)

https://github.com/ProteinsWebTeam/ebi-metagenomics-cwl.git

Path: workflows/emg-pipeline-v3-paired.cwl

Branch/Commit ID: 56dafa4