nanomethphase 0.1

Phase long reads from Oxford Nanopore Technologies based on their methylated profile.

NanoMethPhase

Phase long reads and CpG methylations from Oxford Nanopore Technologies.

Installation

Using pypi repository

pip install nanomethphase

Using conda

TBD

From source

git clone https://github.com/vahidAK/NanoMethPhase.git
cd NanoMethPhase
./nanomethphase.py

Creating a dedicated conda environment

Environment file available in the git repository

git clone https://github.com/vahidAK/NanoMethPhase.git
conda env create -f NanoMethPhase/envs/environment.yaml

Quickstart

If you have your methylation call data and phased vcf file you can get the haplotype methylome via:

1- Processing and indexing methylation call file

nanomethphase methyl_call_processor -mc MethylationCall.tsv -t 20 | sort -k1,1 -k2,2n -k3,3n | bgzip > MethylationCall.bed.gz && tabix -p bed MethylationCall.bed.gz

2- Getting haplotype methylome:

nanomethphase phase -mc MethylationCall.bed.gz -o Test_methylome -of bam,methylcall,bam2bis -b sorted.bam -r hg38.fa -v Phased.vcf -t 64

You can select 3 output options:

bam: output phased bam files

methylcall: output phased methylation call and frequency files

bam2bis: output mock whole-genome bisulfite converted bam files

Full Tutorial

In order to get the phased methylome you also need the following third-party software:

Nanopolish : To call CpG methylation.

Clair or other variant callers: To call variants for your sample. Alternatively, you might already have variant calling data for example from Illumina sequencing.

WhatsHap: To phase single nucleotide variants.

Methylation Calling

1- indexing fastq file and fast5 files:

NOTE: Fastqs must be merged to a single file

nanopolish index -d /path/to/fast5s_directory/.fastq

2- Methylation calling for CpG from each read:

nanopolish call-methylation -t <number of threads> -q cpg -r /path/to/fastq_fromstep-1/fastq.fastq -b /path/to/sorted_and_indexed/bam.bam -g /path/to/reference.fa > /path/to/MethylationCall.tsv

For the full tutorial please refer to Nanopolish page on GitHub.

Variant Calling

We have used Clair to call variants. However, you may call variants with other tools or your variant data may come from Illumina or other methods.

You can call variants for each chromosome using the following command and the concatenate all files:

for i in chr{1..22} chrX chrY; do callVarBam --chkpnt_fn <path to model file> --ref_fn <reference_genome.fa> --bam_fn <sorted_indexed.bam> --ctgName $i --sampleName <your sample name> --call_fn $i".vcf" --threshold 0.2 --samtools <path to executable samtools software> --pypy <path to executable pypy > --threads <number of threads>

For the full tutorial please refer to Clair page on GitHub.

After variant calling, you can select only SNVs which will be used for phasing: awk '$4 != "." && $5 != "." && length($4) == 1 && length($5) == 1' && $6 > <the variant calling quality threshold> variants.vcf > HighQualitySNVs.vcf

If you are calling variants from low coverage nanopore data (<30x) using Clair, you can also use our other tool SNVoter to improve SNV detection.

Phasing of detected SNVs

If you have your SNVs data available you need to phase them using WhatsHap.

whatshap phase --ignore-read-groups --reference reference.fa -o HighQualitySNVs_whatshap_phased.vcf HighQualitySNVs.vcf sorted_indexed.bam

For the full tutorial please refer to WhatsHap page on GitHub.

If you have Trio data (Father, Mother, Child) you can use the script Trio_To_PhaseVCF_4FemaleChild.sh or Trio_To_PhaseVCF_4MaleChild.sh script to make a mock phased vcf file and use it as input for NanoMethPhase.

Detecting Haplotype Methylome

1- First you need to phase process methylation call file from Nanopolish.

nanomethphase methyl_call_processor -mc MethylationCall.tsv -t 20 | sort -k1,1 -k2,2n -k3,3n | bgzip > MethylationCall.bed.gz && tabix -p bed MethylationCall.bed.gz

2- Getting haplotype methylome:

nanomethphase phase -mc MethylationCall.bed.gz -o Test_methylome -of bam,methylcall,bam2bis -b sorted.bam -r hg38.fa -v Phased.vcf -t 64

If your are not using called SNVs from nanopore data, and they come from, for example, short-read sequencing, we recommend using -mbq 0 in the above code.

You can select 3 output options:

bam: output phased bam files

methylcall: output phased methylation call and frequency files

bam2bis: output mock whole-genome bisulfite converted bam files

3- Differential Methylation Analysis:

nanomethphase dma -c 1,2,4,5,7 -ca <path to output methylation frequency for haplotype1> -co <path to output methylation frequency for haplotype2> -rs <path to executable Rscript> -sf /projects/vakbari_prj/scratch/BitBucket/NanoMethPhase/DSS_DMA.R -o . -op Aicardi_NanoMethPhase_DMA

To findout about different modules run:

nanomethphase -h

For a full list of options and help for each module run:

nanomethphase <module name> -h