GetMinPairwiseCor | R Documentation |
Filter the contiguous co-edited subregions found from
FindCorrelatedRegions
, by calculating pairwise correlations
and then selecting subregions passing the minimum correlation filter.
GetMinPairwiseCor( rnaEditCluster_mat, minPairCorr = 0.1, probes_ls, method = c("spearman", "pearson") )
rnaEditCluster_mat |
A matrix of RNA editing level values on individual sites, with row names as sample IDs and column names as site IDs in the form of "chrAA:XXXXXXXX". |
minPairCorr |
Minimum pairwise correlation coefficient of sites within a cluster, used as a filter. To use this filter, set a number between -1 and 1 (defaults to 0.1). To turn it off, please set the number to -1. |
probes_ls |
A list of regions with sites. Please note that probes in each list need to be ordered by their locations. |
method |
Method for computing correlation. Defaults to
|
A list with a list of probes passing the minPairCorr and a data frame with the following columns:
subregion
: index for each output contiguous co-edited
region.
keepminPairwiseCor
: indicator for contiguous co-edited
subregions, The regions with keepminPairwiseCor = 1
passed the
minimum correlation and will be returned as a contiguous co-edited
subregion.
minPairwiseCor
: the minimum pairwise correlation of
sites within a subregion.
data(t_rnaedit_df) ordered_cols <- OrderSitesByLocation( sites_char = colnames(t_rnaedit_df), output = "vector" ) exm_data <- t_rnaedit_df[, ordered_cols] exm_sites <- list( "1" = c("chr1:28661656", "chr1:28661718", "chr1:28662148") ) GetMinPairwiseCor( rnaEditCluster_mat = exm_data, minPairCorr = 0.1, probes_ls = exm_sites, method = "spearman" )
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