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Load Summary Statistics for Normalized Expression Data

load_summary_stats.Rd

Loads group- and timepoint-level summary statistics for normalized expression data across tissues, molecular assays, and analytical platforms. Summary statistics consist of means and standard deviations computed within randomization groups and timepoints. Limited to the initial acute bout, training data is excluded here.

These datasets are intended for descriptive and exploratory analyses. Sample-level data are not distributed with this package and are available upon request via https://motrpac-data.org.

For metabolomics assays, summary statistics are computed after filtering redundant metabolites; see the Methods section of the associated documentation for details.

Usage

load_summary_stats(
  selected_tissues = "all",
  selected_omes = "all",
  single_matrix = FALSE,
  verbose = TRUE
)

Arguments

selected_tissues

character; tissues to include. One or more of "adipose", "blood", "muscle", or "all".

selected_omes

character; molecular assays to include. One or more of "transcript-rna-seq", "prot-pr", "prot-ph", "prot-ol", "epigen-atac-seq", "epigen-methylcap-seq", "metab", or "all". Selecting "metab" loads all metabolomics platforms.

single_matrix

logical; if TRUE, returns a single combined data.frame across all selected tissues and assays. If FALSE (default), returns a nested list.

verbose

logical; toggle verbosity.

Value

If single_matrix = FALSE, a nested list of data.frame objects. The top-level names correspond to tissues, and the second-level names correspond to assays or platforms.

If single_matrix = TRUE, a single data.frame containing all selected summary statistics, with missing columns filled as NA.

Details

Summary statistics were filtered to only those that qualified for differential analysis. This means for proteomics/phosphoproteomics, samples required a paired n>=3 to be included. See the methods in the manuscript for more information. In epigenetic assays, features were filtered for significant features (FDR<0.05) for file size purposes.

Author

Christopher Jin

Examples

if (FALSE) { # \dontrun{
## Load all summary statistics
sum_stats = load_summary_stats()

## Load metabolomics only
metab_stats = load_summary_stats(selected_omes = "metab")

## Load adipose transcriptomics as a single table
adipose_rna = load_summary_stats(
  selected_tissues = "adipose",
  selected_omes = "transcript-rna-seq",
  single_matrix = TRUE
)
} # }