Explore metadata by gene expression on the sex chromosomes (PCA)

Principal Component Analysis (PCA) of sex-specific genes. Samples greater than z standard deviations (SDs) from the mean of sample sub-groups identified as outliers.

plot_sexcheck_pca(clean_metadata, count_df, biomart_results, sex_var)

Arguments

clean_metadata

A data frame with sample identifiers as rownames and variables as factors or numeric as determined by "sageseqr::clean_covariates()".

count_df

A counts data frame with sample identifiers as column names and gene Ids are rownames.

biomart_results

Output of "sageseqr::get_biomart()". Gene Ids are stored as rownames.

sex_var

Column name of the sex or gender-specific metadata.