correlation_matrices_example: Correlation matrices

In DrDimont: Drug Response Prediction from Differential Multi-Omics Networks

Correlation matrices

Description

Exemplary intermediate pipeline output: Correlation matrices example data built by compute_correlation_matrices using layers_example data and settings:

Usage

correlation_matrices_example

Format

A named list with 2 items.

correlation_matrices

A named list with two groups.

groupA

Correlation matrices associated with 'groupA'

mrna

Correlation matrix

protein

Correlation matrix

phosphosite

Correlation matrix

metabolite

Correlation matrix

groupB

same structure as 'groupA'

annotations

A named list containing data frames of mappings of assigned node IDs to the user-provided component identifiers for nodes in 'groupA' or 'groupB' and all nodes

groupA

Annotations associated with 'groupA'

mrna

Data frame

protein

Data frame

phosphosite

Data frame

metabolite

Data frame

groupB

same structure as 'groupA'

both

same structure as 'groupA'

Details

settings <- drdimont_settings( handling_missing_data=list( default="pairwise.complete.obs", mrna="all.obs"))

A subset of the original data from Krug et al. (2020) and randomly sampled metabolite data in layers_example was used to generate the correlation matrices. They were created from data stratified by estrogen receptor (ER) status: 'groupA' contains data of ER+ patients and 'groupB' of ER- patients.

Source

Krug, Karsten et al. “Proteogenomic Landscape of Breast Cancer Tumorigenesis and Targeted Therapy.” Cell vol. 183,5 (2020): 1436-1456.e31. doi:10.1016/j.cell.2020.10.036

DrDimont documentation built on Sept. 23, 2022, 5:06 p.m.