This function allows to calculate Intra-donor variations in bulk data over longitudinal timepoints. The coefficient of variation (CV=SD/mean) is calculated in Bulk data in same donor/participant across timepoints.
cvCalcBulk(
data_object,
meanThreshold = 1,
cvThreshold = 5,
median_cvThreshold = NULL,
donorThreshold = NULL,
housekeeping_genes = NULL,
naThreshold = 1,
plot_log10 = FALSE,
selectedFeatures = NULL,
median_cv_max = NULL,
plotWidth = 5,
plotHeight = 8,
fileName = NULL,
filePATH = NULL
)PALMO object with CV list
Input PALMO S4 object. Contains annotation table and expression matrix or data frame. Rows represent gene/proteins column represents participant samples (same as annotation table Sample column)
Average expression threshold to filter lowly expressed genes Default is 1 (log2 scale)
Coefficient of variation threshold to select variable and stable genes. Default is 5 for bulk data. Users can use 10-20 for single cell average expression data.
Optional, median of CVs from each donor/participant calculated. Threshold used to differentiate variable and stable features across donors/participants. Default, same as cvThreshold.
Donor threshold number to be used, Default is number of participants
Optional, vector of housekeeping genes. Default is c("ACTB", "GAPDH")
Optional, For a give feature % of donors/participants showing non-NA CVs (NAs appear due to expression ~0 or absent). Default is 1 means all donors/participants to consider. 0.5 means from 4 donors atleast 2 donors should have non-NA CVs for a given feature.
Optional, Plot CV vs Mean on log10 scale. Default FALSE
Optional, focus on selected genes/features.
Optional, Remove features with greater than median CV Default is NULL
Optional, heat plot width 5 in
Optional, heat plot height 8 in
User-defined file name, Default outputFile
User-defined output directory PATH Default, current directory
if (FALSE) {
palmo_obj=cvCalcBulk(data_object=palmo_obj, meanThreshold=0.1, cvThreshold=5)
}
Run the code above in your browser using DataLab