Forum:Gallery: Computational tools for DNA methylation

Question

[Shicheng Guo]

More suggestions? 

BeadScan: Analysing data from Illumina BeadArrays
BisReadMapper: Library-free methylation sequencing with bisulfite padlock 
BRAT: Highly configurable and well-documented three‑letter bisulphite aligner
BSMAP: Probably the most widely used wild-card bisulphite aligner
BSmooth is a pipeline for analyzing WGBS data: aligning, quality control, and identifying DMRs.
ComBat: R script for correcting known or suspected batch effects 
DMAP: differential methylation analysis package for RRBS and WGBS data.
GenomeStudio: GenomeStudio Methylation Module v1.8
GSNAP: Wild-card bisulphite aligner included in a widely used general-purpose
isva: R package for batch effect correction using an algorithm
MethylCoder: Three‑letter bisulphite aligner that can be used with either Bowtie and Bowtie2 
methylumi: R/Bioconductor package for Infinium data normalization
minfi: R/Bioconductor package for Infinium data normalization, analysis
Pash: Wild-card bisulphite aligner included in a general-purpose alignment tool 
RMAP: Wild-card bisulphite aligner included in a general-purpose alignment tool
RnBeads: R package providing a software pipeline for Infinium data normalization,
RRBSMAP: Variant of BSMAP that is specialized on reduced-representation
segemehl: Wild-card bisulphite aligner included in a general-purpose alignment tool
SVA: R/Bioconductor package for correcting batch effects
methyLiftover: cross-platform DNA methylation data integration
dariober's methylation-cafe: https://github.com/dariober/bioinformatics-cafe
metilene for DMR (Fast and Sensitive: better than MOABS and Bsmooth)http://www.bioinf.uni-leipzig.de/Software/metilene/Downloads/
scLVM: single-cell RNA-seq heterogeneity source deconvolution
methpipe: http://smithlabresearch.org/software/methpipe/
Bis-SNP: http://people.csail.mit.edu/dnaase/bissnp2011/
COMETs: Information recovery from low coverage whole-genome bisulfite sequencing
HMMcopy: copy number estimations for whole genome data with GC and mappability correction
BS-SNPer: SNP calling in bisulfite-seq data

Answer 1

[David Langenberger]

metilene (Link)

References:

• Jühling F, Kretzmer H, Bernhart SH, Otto C, Stadler PF, Hoffmann S., "metilene: fast and sensitive calling of differentially methylated regions from bisulfite sequencing data.", Genome Res. 2016 Feb;26(2):256-62.
• Kretzmer et al., "DNA methylome analysis in Burkitt and follicular lymphomas identifies differentially methylated regions linked to somatic mutation and transcriptional control.", Nat Genet. 2015 Nov;47(11):1316-25.

[forever]

DNA methylation needs 5 stages: Mapping and Normalization Preprocessing Analysing Visualisation Validation and interpretation Partek company has a software for all these stages but it is not free. My question is: 1- Which of the current packages have the five stages with different options? 2- I need a tutorial to follow to reproduce some figures like? Thank you

Answer 2

[Antonio R. Franco]

Bismark?

BiSeq (under R)

Answer 3

[Sandeep]

• dna-bison - Bisulfite alignment On Nodes of a cluster
• NextGenMap - Has a methylation specific mapper
• bwa-meth - Align BS-Seq reads and extract methylation without intermediate temp files
• BiQ analyser - Easy visualization and quality control of DNA methylation

Answer 4

[dariober]

...Since this thread as returned to the top, here's my 2p.

I wrote a simple parser to extract methylation from bam files, bam2methylation.py

Answer 5

[Ron]

methyAnalysis :https://www.bioconductor.org/packages/devel/bioc/vignettes/methyAnalysis/inst/doc/methyAnalysis.pdf

methylKit: https://github.com/al2na/methylKit

MethylMix:https://www.bioconductor.org/packages/release/bioc/html/MethylMix.html

missMethyl: http://bioconductor.org/packages/release/bioc/html/missMethyl.html

Some more tools to analyze Differentially methylated regions (DMRs) : https://omictools.com/differentially-methylated-regions-category

Answer 6

[william.bill.langdon]

The latest version of BarraCUDA (ie 0.7.107f http://sourceforge.net/projects/seqbarracuda/, effectively BWA on CUDA hardware) can be used with epigenetics NGS data on graphics cards. However note that currently epigenetics data effectively doubles the size of the memory needed for the reference genome, so for human data you may need a GPU with more than 6GB. For noisy data, you might want to increase the allowed number of mismatches (option -n). Bill

Answer 7

[william.bill.langdon]

New technical report RN/16/10 https://doi.org/10.1101/095075 gives BarraCUDA performance on nvidia Titan X (pascal), GTX 1080 and Titan X (compute level 5.2) graphics cards on paired end Cambridge Epigenetix data. Bill

Answer 8

[william.bill.langdon]

BioData Mining has just published our "Short Report" on Genetically improved BarraCUDA. Bill

Answer 9

[Antonio R. Franco]

cgmaptools, a collection of programs to handle methylation data

Answer 10

[Naz]

For Analysis: MethylKit , For data visualization: SeqMonk