sequencing.annotate: Annotate a bisulfite sequencing experiment (WGBS or RRBS)...
In DMRcate: Methylation array and sequencing spatial analysis methods

Description Usage Arguments Value Author(s) References Examples

Either: - Annotate a BSseq object with chromosome position and test statistic, or - Parse output from DSS::DMLtest() or DSS::DMLtest.multiFactor() into a CpGannotated object.

1 2	sequencing.annotate(obj, methdesign, all.cov=FALSE, contrasts = FALSE, cont.matrix = NULL, fdr = 0.05, coef, ...)

`obj`	A BSseq object or data.frame output from `DSS::DMLtest()` or `DSS::DMLtest.multiFactor()`.
`methdesign`	Methylation study design matrix describing samples and groups. Use of edgeR::modelMatrixMeth() to make this matrix is highly recommended, since it transforms a regular model.matrix (as one would construct for a microarray or RNA-Seq experiment) into a “two-channel” matrix representing methylated and unmethylated reads for each sample. Only applicable when `obj` is a BSseq object.
`all.cov`	If `TRUE`, only CpG sites where all samples have > 0 coverage will be retained. If `FALSE`, CpG sites for which some (not all) samples have coverage=0 will be retained.
`contrasts`	Logical denoting whether a `limma`-style contrast matrix is specified. Only applicable when `obj` is a BSseq object.
`cont.matrix`	`Limma`-style contrast matrix for explicit contrasting. For each call to `sequencing.annotate`, only one contrast will be fit. Only applicable when `obj` is a BSseq object.
`fdr`	FDR cutoff (Benjamini-Hochberg) for which CpG sites are individually called as significant. Used to index default thresholding in dmrcate(). Highly recommended as the primary thresholding parameter for calling DMRs. Only applicable when `obj` is a BSseq object.
`coef`	The column index in `design` corresponding to the phenotype comparison. Corresponds to the comparison of interest in `design` when `contrasts=FALSE`, otherwise must be a column name in `cont.matrix`. Only applicable when `obj` is a BSseq object.
`...`	Extra arguments passed to the `limma` function lmFit(). Only applicable when `obj` is a BSseq object.

A CpGannotated-class.

Tim J. Peters <t.peters@garvan.org.au>

Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015). limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Research, 43(7), e47.

Chen, Y., Pal, B., Visvader, J. E., & Smyth, G. K. (2017). Differential methylation analysis of reduced representation bisulfite sequencing experiments using edgeR. F1000Research, 6, 2055.

library(ExperimentHub)
library(SummarizedExperiment)
eh = ExperimentHub()
bis_1072 <- eh[["EH1072"]]
pData(bis_1072) <- data.frame(replicate=gsub(".*-", "", colnames(bis_1072)),
                              tissue=substr(colnames(bis_1072), 1, nchar(colnames(bis_1072))-3), 
                              row.names=colnames(bis_1072))
colData(bis_1072)$tissue <- gsub("-", "_", colData(bis_1072)$tissue)
bis_1072 <- renameSeqlevels(bis_1072, mapSeqlevels(seqlevels(bis_1072), "UCSC"))
bis_1072 <- bis_1072[seqnames(bis_1072)=="chr19",]
bis_1072 <- bis_1072[240201:240300,]
tissue <- factor(pData(bis_1072)$tissue)
tissue <- relevel(tissue, "Liver_Treg")
design <- model.matrix(~tissue)
colnames(design) <- gsub("tissue", "", colnames(design))
colnames(design)[1] <- "Intercept"
rownames(design) <- colnames(bis_1072)
methdesign <- edgeR::modelMatrixMeth(design)
cont.mat <- limma::makeContrasts(treg_vs_tcon=Lymph_N_Treg-Lymph_N_Tcon,
                                 fat_vs_ln=Fat_Treg-Lymph_N_Treg,
                                 skin_vs_ln=Skin_Treg-Lymph_N_Treg,
                                 fat_vs_skin=Fat_Treg-Skin_Treg,
                                 levels=methdesign)
seq_annot <- sequencing.annotate(bis_1072, methdesign, all.cov = TRUE, 
                                   contrasts = TRUE, cont.matrix = cont.mat, 
                                   coef = "treg_vs_tcon", fdr=0.05)