Joint multi-omics dimensionality reduction approaches for CAKUT data using peptidome and proteome data

Brief description In (Cantini et al. 2020), Cantini et al. evaluated 9 representative joint dimensionality reduction (jDR) methods for multi-omics integration and analysis and . The methods are Regularized Generalized Canonical Correlation Analysis (RGCCA), Multiple co-inertia analysis (MCIA), Multi-Omics Factor Analysis (MOFA), Multi-Study Factor Analysis (MSFA), iCluster, Integrative NMF ...

For integrative analysis of CAKUT multi-omics data DIABLO method of the mixOmics package (version 6.10.9. Singh et. al. 2019) was used with sPLS-DA (sparse Partial Least Squares Discriminant Analysis Discriminant Analysis) and PLS-DA classification.

In this analysis, we created an extended pathway, using the WikiPathways repository (Version 20210110) and the three -omics datasets. For this, each of the three -omics datasets was first analyzed to identify differentially expressed elements, and pathways associated with the significant miRNA-protein links were detected. A miRNA-protein link is deemed significant, and may possibly be implying causality, if both a miRNA and its target are significantly differentially expressed.

The peptidome and ...

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")

StructuralVariants Workflow

Snakemake workflow: FAIR CRCC - image conversion

A Snakemake workflow for converting whole-slide images (WSI) from the CRC Cohort ...

Snakemake workflow: dna-seq-varlociraptor

A ...