## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- library(methylSig) ## ----eval = FALSE------------------------------------------------------------- # meth = methylSigReadData( # fileList = files, # pData = pData, # assembly = 'hg19', # destranded = TRUE, # maxCount = 500, # minCount = 10, # filterSNPs = TRUE, # num.cores = 1, # fileType = 'cytosineReport') ## ----read--------------------------------------------------------------------- files = c( system.file('extdata', 'bis_cov1.cov', package='methylSig'), system.file('extdata', 'bis_cov2.cov', package='methylSig') ) bsseq_stranded = bsseq::read.bismark( files = files, colData = data.frame(row.names = c('test1','test2')), rmZeroCov = FALSE, strandCollapse = FALSE ) ## ----filter_by_coverage------------------------------------------------------- # Load data for use in the rest of the vignette data(BS.cancer.ex, package = 'bsseqData') bs = BS.cancer.ex[1:10000] bs = filter_loci_by_coverage(bs, min_count = 5, max_count = 500) ## ----filter_by_location------------------------------------------------------- # Construct GRanges object remove_gr = GenomicRanges::GRanges( seqnames = c('chr21', 'chr21', 'chr21'), ranges = IRanges::IRanges( start = c(9411552, 9411784, 9412099), end = c(9411552, 9411784, 9412099) ) ) bs = filter_loci_by_location(bs = bs, gr = remove_gr) ## ----eval = FALSE------------------------------------------------------------- # # For genomic windows, tiles = NULL # windowed_meth = methylSigTile(meth, tiles = NULL, win.size = 10000) # # # For pre-defined tiles, tiles should be a GRanges object. ## ----tile_by_windows---------------------------------------------------------- windowed_bs = tile_by_windows(bs = bs, win_size = 10000) ## ----tile_by_regions---------------------------------------------------------- # Collapsed promoters on chr21 and chr22 data(promoters_gr, package = 'methylSig') promoters_bs = tile_by_regions(bs = bs, gr = promoters_gr) ## ----eval = FALSE------------------------------------------------------------- # result = methylSigCalc( # meth = meth, # comparison = 'DR_vs_DS', # dispersion = 'both', # local.info = FALSE, # local.winsize = 200, # min.per.group = c(3,3), # weightFunc = methylSig_weightFunc, # T.approx = TRUE, # num.cores = 1) ## ----filter_by_group_coverage------------------------------------------------- # Look a the phenotype data for bs bsseq::pData(bs) # Require at least two samples from cancer and two samples from normal bs = filter_loci_by_group_coverage( bs = bs, group_column = 'Type', c('cancer' = 2, 'normal' = 2)) ## ----diff_methylsig----------------------------------------------------------- # Test cancer versus normal with dispersion from both groups diff_gr = diff_methylsig( bs = bs, group_column = 'Type', comparison_groups = c('case' = 'cancer', 'control' = 'normal'), disp_groups = c('case' = TRUE, 'control' = TRUE), local_window_size = 0, t_approx = TRUE, n_cores = 1) ## ----eval = FALSE------------------------------------------------------------- # contrast = matrix(c(0,1), ncol = 1) # result_dss = methylSigDSS( # meth = meth, # design = design1, # formula = '~ group', # contrast = contrast, # group.term = 'group', # min.per.group=c(3,3)) ## ----filter_by_group_coverage2, eval = FALSE---------------------------------- # # IF NOT DONE PREVIOUSLY # # Require at least two samples from cancer and two samples from normal # bs = filter_loci_by_group_coverage( # bs = bs, # group_column = 'Type', # c('cancer' = 2, 'normal' = 2)) ## ----diff_dss_fit_simple------------------------------------------------------ # Test the simplest model with an intercept and Type diff_fit_simple = diff_dss_fit( bs = bs, design = bsseq::pData(bs), formula = as.formula('~ Type')) ## ----diff_dss_test_simple----------------------------------------------------- # Test the simplest model for cancer vs normal # Note, 2 rows corresponds to 2 columns in diff_fit_simple$X simple_contrast = matrix(c(0,1), ncol = 1) diff_simple_gr = diff_dss_test( bs = bs, diff_fit = diff_fit_simple, contrast = simple_contrast, methylation_group_column = 'Type', methylation_groups = c('case' = 'cancer', 'control' = 'normal')) ## ----sessionInfo-------------------------------------------------------------- sessionInfo()