compute_pop_dm_table: Compute differential mehylation table for each probe...

In magrichard/dmprocr: A R package that performs differential methylation profiles clustering

Compute differential mehylation table for each probe according to population-level analysis (tested samples VS control).

Description

Generate differential methylation data table from beta values. It basically extract all tumorous samples and controls. Then it computes the difference between each tumorous and the mean of control.

Usage

compute_pop_dm_table(gene_list, exp_grp, data_meth,
  filter_indiv = "no_filter", contrast = c("tissue_status", "patho",
  "normal"), pf_meth, pf_pos_colname, pf_chr_colname, updwn_str = 5000,
  slide = 0, apply_func = apply)

Arguments

gene_list	A gene_list bedfile containing the genes to screen for differential methylation.
exp_grp	A exp_grp dataframe that contains metadatas on individuals and samples.
data_meth	A meth matrix that contains methylation information (beta values). Columns correspond to indivuals, row correspond to probes.
filter_indiv	A vector of individual names to be screened for differential expression. Optionnal (set on "no_filter" by default).
contrast	A vector containing the constrast to use to estimate the differential methylation. By default: c("tissue_status","patho","normal")
pf_meth	A data frame describing CpG positions.
pf_pos_colname	String matching the name of the column in the platform that contain the position information of probes.
pf_chr_colname	String matching the name of the column in the platform that contain the chromosome on which we find a probes.
updwn_str	An integer specifying up and down stream size (in bp). By default set on 5000pb.
slide	The maximum width slide allowed when comparing two curves. By default set on 0.
apply_func	A function to be used as/instead of R base::apply. By default set on base::apply.

Value

A matrix of differential methylation values based on population analysis.

magrichard/dmprocr documentation built on July 21, 2023, 11:01 p.m.