Introduction

It is known that DNA methylation plays important roles in regulation of cell development and differentiation. DNA methylation/unmethylation mechanisms are common in all tissue/cell. However, different cell types with the same genome have different methylomes. Recently, high-throughput sequencing combining bisulfite treatment (Bisulfite -Seq) have been used to generate DNA methylomes from a wide range of human tissue/cell types at a genome-wide perspective. To characterize the genome regions that consist of continuous CpGs with similar methylation specificity, we developed the Specific Methylation Analysis and Report Tool (SMART) based on the quantified methylation specificity, Euclidean distance and similarity entropy. SMART aims to segment the genome into different functional regions based on the methylation pattern in multiple cell types. Continuous scanning is firstly carried out to obtain the primary segments composed by CpG sites with high methylation similarity across all cell types. Then, the primary segments those localize in close proximity and share similar methylation pattern are merged into different types of segments including high specificity segment (HighSpe), low specificity segment (LowSpe) and almost no cell-specificity segment (NoSpe). At last, the cell-type-specific methylation marks were identified to facilitate the epigenetic analysis.

Install

Please check the file ‘INSTALL’ in the distribution.

Usage of SMART

usage:

SMART MethyDir CytosineDir [-h] [-n PROJECTNAME] [-o OUTPUTFOLDER] [-v]

Example

SMART /usr/local/lib/python2.7/dist-packages/SMART/Example/BSSeq_fortest/ /usr/local/lib/python2.7/dist-packages/SMART/Example/CLoc_hg19_fortest/ -n Test -o /usr/local/lib/python2.7/dist-packages/SMART/Example/Example_Results/

cd  ..\Python27\Scripts\
python SMART ..\Python27\Lib\site-packages\SMART\Example\BSSeq_fortest\ ..\Python27\Lib\site-packages\SMART\Example\CLoc_hg19_fortest\ -n Test -o ..\Python27\Lib\site-packages\SMART\Example\Example_Results\

Output Files

1. Folder SplitedMethy is a a output directory to store the splited Methylation data. The methylation data are stored in different chromosome sub-folders. In each sub-folder, the methylation data for all samples are included.

2. Folder MethylationSpecificity is a output directory to store the methylation levels and specifity for each C which is common across all samples. These files are stored in chromosomes. In this folder, MethylationSpecificity.wig.gz includes the methylation specifity of all common C. And this file can be uploaded to UCSC browser for visualization.

3. Folder MethylationSegment includes three sub-folders: GenomeSegment, GenomeSegmentMethy, and MergedGenomeSegment. The sub-folder GenomeSegment stores all small segments identified by SMART in each chromosome. And the sub-folder GenomeSegmentMethy stores the methylation levels of each small segments across all samples which may be useful for users’ local further analysis. The sub-folder MergedGenomeSegment stores the larger segments merged based on the small segments in each chromosome. The final results are generated based on these merged segments.

4. Folder FinalResults includes all intresting results which may be concerned by users. In this folder, there are six files.

   -The first file 1SmallSegmentBed.txt.gz stores all small segments in bed format, which can be uploaded to UCSC browser for visualization.

   -The second file 2MergedSegmentBed.txt.gz stores all merged segments in bed format, which can be uploaded to UCSC browser for visualization.

   -The third file 3MergedSegment.txt stores all merged segments in txt format, which is useful for local further analysis.

   -The fourth file 4MergedSegmentwithmethylation.txt stores the methylation levels of all merged segments across all samples, which is useful for local further analysis.

   -The fifth file 5MergedHighLowSpeSegmentwithspecificity.txt stores the methylation specificity and p values of t-test for each merged HighSpe/LowSpe segement, which is useful for further analysis on cell-type-specificity for each HighSpe/LowSpe segement. The positive p value represents the segment is hyper-methylated in the corresbonding cell-type, while the negative p value represents the segment is hypo-methylated in the corresbonding cell-type.

   -The sixth file 6CellTypeSpecificMethymarkPvalue.txt is a reformated file for the fifth file. In this file, only the HighSpe/LowSpe segements which show significant hypo- or hyper-methylation in some cell-types are remained. This file is usefull for users to select and analyze cell-type-specific methylation marks including HypoMarks and HyperMarks.

Other useful links

Predefined C locations in various species and other resources:

http://fame.edbc.org/smart/index.html

QDMR:

http://bioinfo.hrbmu.edu.cn/qdmr/

UCSC Genome browser:

http://genome.ucsc.edu/

Contact

For any help:

you are welcome to write to Hongbo Liu (hongbo919@gmail.com).