This is a pre-production deployment of Warehouse. Changes made here affect the production instance of PyPI (pypi.python.org).
Help us improve Python packaging - Donate today!

Identifying focal full methylation of cell subpopulation and inferring fraction

Project Description

CellMethy_v1

DNA methylation patterns within a cell population from individual somatic tissues are highly heterogeneous and polymorphic. We developed CellMethy method to quantify fraction of focal full methylation of cell subpopulation (FMC fraction) and identify fully methylated regions of cell subpopulation (CellMethy) based on single base resolution DNA methylation data. This script is used for infering fraction of focal full methylation cell subpopulation.

Easy to start:

Inputfile: File sepearated by “\t” after bismark processed including read id, strand, chromosome, position of CpGc and methylation state (Z or z).

The result would be placed into input folder: outputfile.

If your fastq mapping is done with bismark and extracted methylation state, use following command:

python CellMethy.py -f inputfile -o outputfile

Options:

-f: The file name of input file after bismark processed, include five columns: read ID, strand, chromosome, position of CpG and methylation states Z (methylated) or z (unmethylated) separated by ‘\t’.

-c: Lowest coverage cutoff in each bin, default is 10.

-b: number of CpGs in each bin, default is 5.

-o: The file name of output file showing full methylation of cell subpopulation, include five columns: chromosome, start, end, FMC fraction, and CpGs number in the region separated by “\t”.

examples:

cd ~/CellMethy-*.*.*
python ./CellMethy/bin/CellMethy.py -f ./data/data_file -b5 -c 10 -o myoutput

How to get Input file

If you have fastq data, you can mapping with bismark tools.

examples:

bismark ./referenceGenome --bowtie2 test.fastq -o test.sam
bismark_methylation_extractor -s --comprehensive test.sam

The output file named “CpG_context_test.txt” is inputfile of CellMethy. The format of CellMethy inputfile include read id, strand, chromosome, position of CpGc and methylation state (Z or z) separated by ‘\t’.

Read1       +       chr21   9827508 Z
Read1       -       chr21   9827503 z
Read1       -       chr21   9827484 z
Read2       +       chr21   9827434 Z
Read2       +       chr21   9827454 Z
Read2       -       chr21   9827483 z
Release History

Release History

This version
History Node

1.2.0

History Node

1.1.27

Download Files

Download Files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
CellMethy-1.2.0.tar.gz (3.2 MB) Copy SHA256 Checksum SHA256 Source Sep 29, 2014

Supported By

WebFaction WebFaction Technical Writing Elastic Elastic Search Pingdom Pingdom Monitoring Dyn Dyn DNS Sentry Sentry Error Logging CloudAMQP CloudAMQP RabbitMQ Heroku Heroku PaaS Kabu Creative Kabu Creative UX & Design Fastly Fastly CDN DigiCert DigiCert EV Certificate Rackspace Rackspace Cloud Servers DreamHost DreamHost Log Hosting