summaryTable {regsplice} | R Documentation |
Display summary table of results from a regsplice
analysis.
summaryTable(rs_results, n = 20, threshold = 0.05, rank_by = c("FDR", "p-value", "none"))
rs_results |
|
n |
Number of genes to display in summary table. Default is 20. If the total
number of significant genes up to the significance threshold is less than |
threshold |
Significance threshold (for either FDR or raw p-values, depending on
choice of argument |
rank_by |
Whether to rank genes by false discovery rate (FDR), raw p-values, or
no ranking. Choices are |
The results of a regsplice
analysis consist of a set of multiple testing
adjusted p-values (Benjamini-Hochberg false discovery rates, FDR) quantifying the
statistical evidence for differential exon usage (DEU) for each gene. Typically, the
adjusted p-values are used to rank the genes in the data set according to their
evidence for DEU, and an appropriate significance threshold (e.g. FDR < 0.05) can be
used to generate a list of genes with statistically significant evidence for DEU.
The main regsplice
functions return results in the form of a
RegspliceResults
object, which contains slots for gene names,
fitted model results, raw p-values, multiple testing adjusted p-values
(Benjamini-Hochberg FDR), likelihood ratio (LR) test statistics, and degrees of
freedom of the LR tests. See RegspliceResults
and the main
regsplice
wrapper function regsplice
for details.
This function generates a summary table of the results. The results are displayed as a
data frame of the top n
most highly significant genes, ranked according to
either FDR or raw p-values, up to a specified significance threshold (e.g. FDR <
0.05).
The argument rank_by
controls whether to rank by FDR or raw p-values. The
default is to rank by FDR.
To display results for all genes up to the significance threshold, set the argument
n = Inf
. To display results for all genes in the data set, set both n =
Inf
and threshold = 1
.
Previous step: Run regsplice
pipeline with the regsplice
wrapper
function (or individual functions up to LRTests
).
Returns a data frame containing results for the top n
most highly
significant genes, up to the specified significance threshold for the FDR or raw
p-values.
file_counts <- system.file("extdata/vignette_counts.txt", package = "regsplice") data <- read.table(file_counts, header = TRUE, sep = "\t", stringsAsFactors = FALSE) head(data) counts <- data[, 2:7] tbl_exons <- table(sapply(strsplit(data$exon, ":"), function(s) s[[1]])) gene_IDs <- names(tbl_exons) n_exons <- unname(tbl_exons) condition <- rep(c("untreated", "treated"), each = 3) rs_data <- RegspliceData(counts, gene_IDs, n_exons, condition) rs_results <- regsplice(rs_data) summaryTable(rs_results) summaryTable(rs_results, n = Inf, threshold = 1)