Biscuiteer User Guide


biscuiteer is package to process output from biscuit into bsseq objects. It includes a number of features, such as VCF header parsing, shrunken M-value calculations (which can be used for compartment inference), and age inference are included. However, the task of locus- and region-level differential methylation inference is delegated to other packages (such as dmrseq).

Quick Start


From Bioconductor,

if (!requireNamespace("BiocManager", quietly=TRUE))

A development version is available on GitHub and can be installed via:

if (!requireNamespace("BiocManager", quietly=TRUE))

Loading Data

biscuiteer can load either headered of header-free BED files produced from biscuit vcf2bed or biscuit mergecg. In either case, a VCF file is needed when loading biscuit output. For practical purposes, only the VCF header is for biscuiteer. However, it is encouraged that the user keep the entire VCF, as biscuit can be used to call SNVs and allows for structural variant detection in a similar manner to typical whole-genome sequencing tools. Furthermore, biscuit records the version of the software and the calling arguments used during processing the output VCF, which allows for better reproducibility.

NOTE: Both the input BED and VCF files must be tabix'ed before being input to biscuiteer. This can be done by running bgzip followed by tabix -p xxx, where xxx is either bed or vcf.

Data can be loaded using the readBiscuit function in biscuiteer:


orig_bed <- system.file("extdata", "MCF7_Cunha_chr11p15.bed.gz",
orig_vcf <- system.file("extdata", "MCF7_Cunha_header_only.vcf.gz",
bisc <- readBiscuit(BEDfile = orig_bed, VCFfile = orig_vcf,
                    merged = FALSE)

Metadata from the biscuit output can be viewed via:


If further information about the VCF header is desired,


Combining Results

In the instance where you have two separate BED files that you would like to analyze in a single bsseq object, you can combine the files using unionize, which is a wrapper around the bsseq function, combine.

shuf_bed <- system.file("extdata", "MCF7_Cunha_chr11p15_shuffled.bed.gz",
shuf_vcf <- system.file("extdata",
bisc2 <- readBiscuit(BEDfile = shuf_bed, VCFfile = shuf_vcf,
                     merged = FALSE)

comb <- unionize(bisc, bisc2)

Analysis Functionality

A handful of analysis paths are available in biscuiteer, including A/B comparment inference, age estimation from WGBS data, hypermethylation of Polycomb Repressor Complex (PRC) binding sites, and hypomethylation of CpG-poor "partially methylated domains" (PMDs).

Inputs for A/B Compartment Inference

When performing A/B compartment inference, the goal is to have something that has roughly gaussian error. getLogitFracMeth uses Dirichlet smoothing to turn raw measurements into lightly moderated, logit-transformed methylated-fraction estimates, which can the be used as inputs to compartmap

reg <- GRanges(seqnames = rep("chr11",5),
               strand = rep("*",5),
               ranges = IRanges(start = c(0,2.8e6,1.17e7,1.38e7,1.69e7),
                                end= c(2.8e6,1.17e7,1.38e7,1.69e7,2.2e7))

frac <- getLogitFracMeth(bisc, minSamp = 1, r = reg)

Age Estimation

biscuiteer has the functionalitity to guess the age of the sample(s) provided using the Horvath-style "clock" models (see Horvath, 2013 for more information).

NOTE: The prediction accuracy of this function is entirely dependent on the parameters set by the user. As such, the defaults (as shown in the example below) should only be used as a starting point for exploration by the user.

NOTE: Please cite the appropriate papers for the epigenetic "clock" chosen: For horvath or horvathshrunk * Horvath, Genome Biology, 2013 For hannum * Hannum et al., Molecular Cell, 2013 * For skinandblood * Horvath et al., Aging, 2018

ages <- WGBSage(comb, "horvath")

Hypermethylation of PRCs and Hypomethylation of PMDs

To generate a shorthand summary of the hypermethylation of PRCs and hypomethylation of PMDs, the CpGindex function in biscuiteer can be used.

bisc.CpGindex <- CpGindex(bisc)

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biscuiteer documentation built on Nov. 8, 2020, 8:28 p.m.