diff_dss_fit: Performs model fit for general experimental design
In methylSig: MethylSig: Differential Methylation Testing for WGBS and RRBS Data

Description Usage Arguments Value Examples

This function is a wrapper for DSS::DMLfit.multiFactor.

1	diff_dss_fit(bs, design, formula)

`bs`	a `BSseq` object to calculate differential methylation statistics.
`design`	a `data.frame` or `DataFrame` for experimental design. Should contain as many rows as there are columns (samples) in `bs`, and the order of the rows should match the columns of `bs`. If omitted, will default to `pData(bs)`.
`formula`	a formula for the linear model. It should refer to column names from `design`. NOTE: The intercept is included by default if omitted. One can omit the intercept with a formula such as `'~ 0 + group'`. For clarity, it helps to include the intercept explicitly as in `'~ 1 + group'`.

A list object with:

gr:: a GRanges object with loci fit.
design:: the data.frame input as the experimental design.
formula:: the formula representing the model. Can be character or formula.
X:: the design matrix used in regression based on the design and formula. This should be consulted to determine the appropriate contrast to use in dss_fit_test().
fit:: a list with model fitting results. It has components beta, the estimated coefficients, and var.beta the estimated variance/covariance matrix for beta.

data(BS.cancer.ex, package = 'bsseqData')

bs = filter_loci_by_group_coverage(
    bs = BS.cancer.ex,
    group_column = 'Type',
    c('cancer' = 2, 'normal' = 2))

small_test = bs[1:50]

diff_fit = diff_dss_fit(
    bs = small_test,
    design = bsseq::pData(bs),
    formula = '~ Type')