DNA Methylation Toolkit

DNA Methylation Toolkit provide reseachers to find out the relationship of methylation in different samples. There are many tools contain is this Toolkit, users can use it discretionary.

Tools in Toolkit

• Heatmap & PCA：
• Differentially Methylated Region：
• Fold Enrichment：
• Differentially Methylated Gene：
• Chromosome View：
• Metaplot：

Before using Toolkit

Before using Toolkit, system requirement and some kits that need to be installed are as follows

• System Requirement

  • CPU：No special restrictions, but CPU has 16 cores is more efficient
  • MEM：12GB or higer (in arabidopsis sample) / 256GB or higher (in human sample)

• Essential Kits

  • Python 2.7 or above
  • Python modules：pandas, numpy, matplotlib, math, scipy, argparse, glob, pyBigWig, collections, gzip, re, PyQt5
  • R 3.5.1 or above
  • bedtools
  • deepTools

Download and install python

for windows

https://www.python.org/downloads/%20windows/

• and choose version which environment you are

for Mac OS X

https://www.python.org/downloads/mac-osx/

• and choose version which environment you are

for Linux (Ubuntu, also in Mac OS X), using command line

sudo apt-get install python2.7

or

sudo apt-get install python3.6

Download and install R

In this link, choose one mirror that is near your location, and choose version which environment you are

https://cran.r-project.org/mirrors.html

or in Mac OS X and Linux, using this command

sudo apt-get install r-base

Download and install pip

for windows

python get-pip.py

for Mac OS X

sudo apt-get install python-pip

for Linux (ubuntu)

sudo apt-get install python-pip

Download and install essential kits

Use the following commands one by one

pip install pandas
pip install numpy
pip install matplotlib
pip install math
pip install scipy
pip install argparse
pip install glob
pip install pyBigWig
pip install collections
pip install gzip
pip install re
pip install PyQt5

How to use

User can choose nongui or gui mode to use this Toolkit

• GUI mode

  • See GUI description.docx for details.

• Non-gui mode using commandline

  • program path：Path of 'nongui.py' (This Toolkits main program(non-gui mode))
  • input_gene_name：Path of input_gene (Your input gene file)
  • Optional Parameters：Analysis parameters. If you not use it, it will setting by default value

python [program path] [input_gene_name] [Optional Parameters]

Parameters of this program

positional arguments:
  input_gene_name           path of input gene

optional arguments:
  -h, --help                show this help message and exit
  -d DEPTH                  min size of #C+#T
  -r REGION                 size of region
  -q QUAIFIED               min number of region member
  -hcgc HEATMAP_CG_CUTOFF   Heatmap_cutoff
  -hchhc HEATMAP_CHH_CUTOFF Heatmap_cutoff
  -hchgc HEATMAP_CHG_CUTOFF Heatmap_cutoff
  -dcgc DMR_CG_CUTOFF       DMR_CG_cutoff
  -dchhc DMR_CHH_CUTOFF     DMR_CHH_cutoff
  -dchgc DMR_CHG_CUTOFF     DMR_CHG_cutoff
  -b BIN_SIZE               resolution of chrView and Metaplot
  -p PROMOTER_SIZE          promoter_size

For example, if a user want to analysis arabidopsis sample, and he want to set region size and dmr's cut off value, he need input this command

python nongui.py arabidopsis.gtf -r 800 -dchhc 0.1 -dchgc 0.02

Users also can choose which tools you want to use.

After setting essential parameters, program will ask you 'OOO Analysis? (y/n)' one by one, if you want use it, just enter 'y'

There are some tools in this Toolkits

• Heatmap & PCA
  • Heatmap：Visualizing methylation level. Easily to overview the methylation level distribution
  • PCA：Which samples from similar environment (have much similar features) will be concentrated
• Differentially Methylated Region (required)
  • Find which regions exist significant methylation level difference
• Differentially Methylated Gene
  • Which genes are ‘overlap’ with DMR. Means find which genes are exist significant methylation level difference
• Chromosome View
  • View the genome wide methylation level distribution by chromosomes
  • Also can view mean difference of samples methylation level between two different group of samples
  • If user choose this tool, program will ask you which group of samples is experimental group and which is control group, user just need enter the group name
• Metaplot
  • View the methylation level distribution on specific genomic feature and its nearby area
  • Also can view mean difference of samples methylation level between two groups
  • If user choose this tool, program will ask you which group of samples is experimental group and which is control group, user just need enter the group name
  • Other than this, program will also ask you choose one specific genomic feature, user just need enter the genomic feature name

The analysis result

Analysis result will be saving in main folder (where is nongui.py in it) in default