DNA methylation is an important epigenetic modification that plays a critical role in most eukaryotic organisms. Parental alleles in haploid genomes may exhibit different methylation patterns, which can lead to different phenotypes and even different therapeutic and drug responses to diseases. However, to our knowledge, no software is available for the identification of DNA methylation haplotype regions. In this paper, we developed a new method, MethHaplo, that identify DNA methylation haplotype regions with allele-specific DNA methylation and single nucleotide polymorphisms (SNPs) from whole-genome bisulfite sequencing (WGBS) data. Our results showed that methylation haplotype regions were ten times longer than haplotypes with SNPs only. When we integrate WGBS and high-throughput chromosome conformation capture (Hi-C) data, MethHaplo could call even longer haplotypes. By constructing methylation haplotypes for various cell lines, we provide a clearer picture of the effect of DNA methylation on gene expression, histone modification and three-dimensional chromosome structure at the haplotype level. Our method could benefit the study of parental inheritance-related disease and heterosis in agriculture.
- gcc (v4.8) , gsl library
- SAMtools
- Python3
- Perl
a) Download
git clone https://github.com/ZhouQiangwei/MethHaplo.git
b) Change directory into the top directory of MethHaplo
cd MethHaplo
c) Type
- make
- make install
d) The binary of MethHaplo will be created in current folder
You can found the test data in ./test dir.
MethHaplo: Combining Allele-specific DNA Methylation and SNPs for Haplotype Region Identification
Usage: methHaplo -M [mode] -a Y/N -m methfile -s <sam>/-b <bam> -o outputprefix
Options:
-M <string> [hap|asm] methHaplo analysis mode
hap: iterative approach, prefer longer haplotype results;
asm: hypergeometric approach, prefer accurate asm results.(default: hap);
-m, --methfile <file> methratio file (requires)
format: chr pos strand context methC coverage methlevel
-o, --out <string> output file prefix
-s, --sam <samfile> sam file from batmeth2-align. This file should be coordinate sorted,
using the <samtools sort> command, and must contain methylstatus[MD:Z:].
-b, --bam <bamfile> bam file, should be coordinate sorted. (use this option or -s option but not both)
-a <Y/N> If bam/sam file contain MD state by batmeth2 calmeth scripts.
If not, please define genome location by -g paramater.
-g, --genome <genome> If bam/sam file isnot contain MD.
-q <int> only process reads with mapping quality >= INT [default >= 20].
-c, --context methylation context process for methHaplo. CG, CHG, CHH, ALL[default].
-C, --NMETH Number of methylated reads cover cytosine site. default: 2 [m>=2]
-N, --NCOVER Number of coverage reads in cytosine site. default: 6 [n >= 6]
-f, --MFloat Cutoff of methratio. default: 0.1 [ f =< meth <= 1-f]
--minIS <INT> Minimum insert size for a paired-end read to be considered as single fragment for phasing, default 0
--maxIS <INT> Maximum insert size for a paired-end read to be considered as a single fragment for phasing, default 1000
--DBtmpsize <INT> Maximum size of temp read store, default 12000. (only useful in asm mode)
--PE Paired-end reads.
-v, --vcffile <file> snp file (optional)
-r, --chromosomal-order Use natural ordering (1,2,10,MT,X) rather then the default (1,10,2,MT,X).
This requires new version of the unix \sort\ command which supports the --version-sort option.
-p, --parallel <int> Change the number of sorts run concurrently to <int>
-t, --temporary-directory Use a directory other than /tmp as the temporary directory for sorting.
-h, -?, --help This help message.
python methpoint.py align.md.sort.bam chrom:start-end strand outputprefix visulsort
[align.md.sort.bam] BS-Seq alignment file for visualization.
[chrom:start-end] The region in chromosome:start-end for visualization.
[strand] visualization strand. [+/-/.]
[outputprefix] output file prefix
[visulsort] Methylation and Unmethylation position in the figure. [0/1]
The figure above represents the distribution of methylation sites in raw reads, orange represents methylation sites, green represents unmethylation sites, and blue represents mutation base information. The bottom figure shows DNA methylation sites and methylation levels.
ASManno [options] -o <OUT_PREFIX> -G GENOME -gff <GFF file>/-gtf <GTF file>/-b <bed file> -ap <asm plus file> -an <asm neg file>
Usage:
-o|--out Output file prefix
-G|--genome Genome
-ap|--asmplus ASM plus file.
-an|--asmneg ASM neg file.
-p|--pvale Pvalue cutoff. default: 0.01
-gtf|-gff Gtf/gff file
-b|--BED Bed file, chrom start end (strand, .bed4 format)
--ped loci file, chrom start (strand, .ped3 format)
-d|--distance ASM distributions in body and <INT>-bp flanking sequences. The distance of upstream and downstream. default:2000
-B|--body For different analysis input format, gene/TEs body methylation level. [Different Methylation Gene(DMG/DMT...)]
-P|--promoter For different analysis input format.[Different Methylation Promoter(DMP)]
-s|--step Gene body and their flanking sequences using an overlapping sliding window of 5% of the sequence length at a step of 0.8% of the sequence length. So default step: 0.008 (0.8%)
-h|--helppython methylevel.py Num Input1.Methylevel.1.txt [Input2 ...] lable outprefix
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