| correlation_matrices_example {DrDimont} | R Documentation |
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