MethylSig DSS test function

[rcavalcante]

Function call

diff_dss_fit(bs, design, formula) diff_dss_test(bs, diff_fit, contrast, methylation_group_column = NA, methylation_groups = NA)

Description

Split tests into fit and test stages to work more like edgeR (for example) and allow users to examine the design matrix prior to making the contrast matrix.

Arguments

• bs a BSseq object possibly having passed through prior filtering and tiling functions.
• design a data.frame giving the experimental design. Rows are samples and columns are phenotype data.
• formula a character string to be coerced to a formula describing the model. The terms of formula should correspond to columns of design. NOTE: The intercept is included by default if omitted, i.e. ~ group is equivalent to ~ 1 + group. One can omit the intercept with a formula such as ~ 0 + group.
• contrast a column vector matrix with as many rows as there are columns in model.matrix(formula, design).
• methylation_group_column a character string indicating the column of the design to use to recover methylation information. Can be a character, factor, or numeric vector.
• methylation_groups a named character vector with names case and control indicating which factors of methylation_group_column to use as case and control. If methylation_group_column is a numeric, omit this and top 25% and bottom 25% samples (based on the covariate) will be used as groups for methylation recovery.

Values

A GRanges object with the following columns always:

• stat
• pvalue
• fdr

And optionally the following columns, depending on presence of methylation_group_column and methylation_groups are given:

• case_meth
• control_meth
• meth_diff

Tests

Test for correct return type.

[rcavalcante]

It would be nice, for continuous covariate tests, to return the methylation rates for the samples that have the top 25% and bottom 25% values for that covariate.