Workflows
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This workflow can be used to fit dose-response curves from normalised cell-based assay data (%confluence) using the KNIME HCS extension. The workflow expects triplicates for each of eight test concentrations. This workflow needs R-Server to run in the back-end. Start R and run the following command: library(Rserve); Rserve(args = "--vanilla"). Three types of outliers can be removed: 1 - Outliers from triplicate measurement (standard deviation cut-off can be selected), 2 - inactive and weekly ...
This workflow can be used to fit dose-response curves from normalised biochemical assay data (%Inhibition) using the HCS extension. This workflow needs R-Server to run in the back-end. Start R and run the following command: library(Rserve); Rserve(args = "--vanilla") IC50 values will not be extrapolated outside the tested concentration range For activity classification the following criteria are applied:
- maximum (average % inhibion) >25 % and slope is >0 and IC50 > 5 µM or
- minimum ...
Generates Dose-response curve fits on cell-based toxicity data. Outliers of replicate data-sets can be removed by setting a threshold for standard deviation (here set to 25). Curve fits for compounds showing low response can be removed by setting a threshold for minimum activity (here set to 75% confluence). This workflow needs R-Server to run in the back-end. Start R and run the following command: library(Rserve); Rserve(args = "--vanilla")
Type: Common Workflow Language
Creators: Pjotr Prins, Andrea Guarracino, Peter Amstutz, Thomas Liener, Adam M. Novak, Bonface Munyoki, Tazro Inutano, Michael Heuer, Michael R. Crusoe, Stian Soiland-Reyes
Submitter: Michael R. Crusoe
StructuralVariants Workflow
Type: Nextflow
Creators: Laura Rodriguez-Navas, Adrián Muñoz-Civico, Daniel López-López
Submitter: Laura Rodriguez-Navas
Snakemake workflow: FAIR CRCC - image conversion
A Snakemake workflow for converting whole-slide images (WSI) from the CRC Cohort ...
Fastq-to-BAM @ NCI-Gadi is a genome alignment workflow that takes raw FASTQ files, aligns them to a reference genome and outputs analysis ready BAM files. This workflow is designed for the National Computational Infrastructure's (NCI) Gadi supercompter, leveraging multiple nodes on NCI Gadi to run all stages of the workflow in parallel, either massively parallel using the scatter-gather approach or parallel by sample. It consists of a number of stages and follows the BROAD Institute's best practice ...
Type: Shell Script
Creators: Cali Willet, Tracy Chew, Georgina Samaha, Rosemarie Sadsad, Andrey Bliznyuk, Ben Menadue, Rika Kobayashi, Matthew Downton, Yue Sun
Submitter: Georgina Samaha
RNASeq-DE @ NCI-Gadi processes RNA sequencing data (single, paired and/or multiplexed) for differential expression (raw FASTQ to counts). This pipeline consists of multiple stages and is designed for the National Computational Infrastructure's (NCI) Gadi supercompter, leveraging multiple nodes to run each stage in parallel.
Infrastructure_deployment_metadata: Gadi (NCI)
A prototype implementation of the Air Quality Prediction pipeline in Galaxy, using CWL tools.