biscuiteer

The original luxury biscuit boutique

Wait, no, that's these guys. biscuiteer, on the other hand, is a package to process biscuit output quickly into bsseq objects. A number of features such as VCF header parsing, shrunken M-value calculations (for compartment inference), and tumor/normal copy number segmentation are also included, but the task of locus- and region-level differential methylation inference is delegated to other packages (such as dmrseq).

Installing

R if (!requireNamespace("BiocManager", quietly=TRUE)) install.packages("BiocManager") BiocManager::install("biscuiteer")

A development version is available on GitHub and can be installed via: R if (!requireNamespace("BiocManager", quietly=TRUE)) install.packages("BiocManager") BiocManager::install("trichelab/biscuiteerData") BiocManager::install("trichelab/biscuiteer")

Usage

Loading data

biscuiteer can load headered or header-free BED-like files as produced from biscuit vcf2bed or biscuit mergecg, but we encourage users to keep their VCF headers (or just the entire VCF, which you will want to do anyways, as biscuit calls SNVs and allows for structural variant detection in a manner similar to typical whole-genome sequencing tools). Since biscuit records the version of the software and the calling arguments used to process a set of files in the output VCF, this allows for much better reproducibility:

```R

Load the package

library(biscuiteer)

To read in some data, you need:

A BED file (with or without a header)

A VCF file (only really needs the header)

Whether the file is merged CG data or not

Any other additional function inputs (genome, region to load, etc)

origbed <- system.file("extdata", "MCF7Cunhachr11p15.bed.gz", package="biscuiteer") origvcf <- system.file("extdata", "MCF7Cunhaheaderonly.vcf.gz", package="biscuiteer") bisc <- readBiscuit(BEDfile = origbed, VCFfile = orig_vcf, merged = FALSE)

To print metadata information from the loaded file:

biscuitMetadata(bisc)

CharacterList of length 3

[["Reference genome"]] hg19.fa

[["Biscuit version"]] 0.1.3.20160324

[["Invocation"]] biscuit pileup -r /primary/vari/genomicdata/genomes/hg19/hg1...

This is all drawn from the VCF header:

metadata(bisc)$vcfHeader

class: VCFHeader

samples(1): MCF7_Cunha

meta(5): fileformat reference source contig program

fixed(1): FILTER

info(3): NS CX N5

geno(7): GT DP ... GL GQ

```

Downstream bits

A/B compartment inference, age estimation from WGBS, and so forth (examples to appear).
To wit, a shorthand summary of hypo- and hyper-methylation at some regions commonly associated with each:

```R bisc.CpGindex <- CpGindex(bisc)

Computing hypermethylation indices...

Loading HMMCpGislands.hg19...

Loading H9state23unmeth.hg19...

Computing hypomethylation indices...

Loading PMDs.hg19.rda from biscuiteerData...

Loading ZhousoloWCGW_inCommonPMDs.hg19.rda from biscuiteerData...

Computing indices...

show(bisc.CpGindex)

CpGindex with 1 row and 3 columns

hyper.MCF7Cunha hypo.MCF7Cunha ratio.MCF7_Cunha

1 0.0690734126984127 0.199261516805161 0.34664702851757

-------

This object is just a DataFrame that has an idea of where it came from:

Hypermethylation was tallied across 120 region (see 'object@hyperMethRegions').

Hypomethylation was tallied across 13127 region (see 'object@hypoMethRegions').

bisc.CpGindex@hyperMethRegions

GRanges object with 120 ranges and 1 metadata column:

seqnames ranges strand | score

|

1 chr1 32230201-32230224 * | 0.0399999991059303

2 chr1 43638401-43638449 * | 0.0399999991059303

3 chr1 44884001-44884005 * | 0.0399999991059303

4 chr1 46860401-46860406 * | 0.0599999986588955

5 chr1 51435801-51436075 * | 0.0499999998137355

... ... ... ... . ...

116 chr20 8112392-8112400 * | 0.0299999993294477

117 chr20 17207801-17208191 * | 0.0599999986588955

118 chr22 20004801-20004802 * | 0.0350000001490116

119 chr22 37252601-37252731 * | 0.0599999986588955

120 chr22 43781850-43781952 * | 0.0449999999254942

-------

seqinfo: 21 sequences from hg19 genome

```

Updating documentation

$ make doc. Requires the roxygen2 package.