timecourseTable: constructs time course table for clustering analysis

In TCseq: Time course sequencing data analysis

Description

This fuction constructs a time course table of which rows corrsponding to genomic features and columns the timepoint. values can be mean normalized read counts or log2-fold changes compared to the first timepoint. The time course table is used for clustering analysis.

Usage

timecourseTable(object, value = "expression", lib.norm = TRUE,
  norm.method = "rpkm", subset = NULL, filter = FALSE, pvalue = "fdr",
  pvalue.threshold = 0.05, abs.fold = 2, direction = "both", ...)

Arguments

object	a TCA object returned by DBanalysis.
value	character string, either 'expression' or 'FC'. 'expression' is the mean normalized read counts of replicates, FC' is the log2-fold changes compared to the first time point.
lib.norm	logical indicating whether or not use effective library size (see 'Details' in counts).
norm.method	character string specifying the normalization method if value is 'expression'
subset	optinal character vector giving a subset of genomic features, if not NULL, time course table is generated for only this subset of genomic features.
filter	logical, whether to drop the genomic features shows no significant changes (defined by pvalue, pvalue.threshold,abs.fold and direction) between any two time points.
pvalue	character string specify the type of p-values ('PValue' or adjusted p-value 'paj')
pvalue.threshold	a numeric value giving threshold of selected p-value, only features with higher (ajusted) p-values than the threshold are kept.
abs.fold	a numeric value, the least absolute log2-fold changes
direction	character string specify the direction of fold changes ('up' (positive fold changes), down' (negative fold changes), both'(both positive and negative fold changes)), features changes more than abs.fold in the defined direction are kept.
...	additional arguments passing to rpkm, cpm

Value

A TCA object

Note

If 'expression' in value is chosen, for replicates , the normalized expression value is first calculated for each replicate, then mean value is taken to represent the normalized expression value.

Author(s)

Mengjun Wu

Examples

data(tca_ATAC)
tca_ATAC <- DBanalysis(tca_ATAC)
tca_ATAC <- timecourseTable(tca_ATAC, value = 'expression',
                            lib.norm = TRUE, norm.method = 'rpkm')

TCseq documentation built on Nov. 8, 2020, 5:46 p.m.