Table 1.
Summary of EWAS‐related tools
| Tools | Detail | Year | Implementation | Software availability | PMID |
|---|---|---|---|---|---|
| Detection of differentially methylated region/loci | |||||
| HPG‐DHunter[ 172 ] | Detection of differentially methylated regions | 2020 | Software | https://grev‐uv.github.io/ | 32631226 |
| DMRcaller[ 173 ] | Differentially methylated regions caller | 2018 | R package | http://bioconductor.org/packages/DMRcaller/ | 29986099 |
| DiMmeR[ 174 ] | Discovery of multiple differentially methylated regions | 2017 | Java package | http://dimmer.compbio.sdu.dk | 27794558 |
| MethylDMV [175] | Detection of differentially methylated regions | 2017 | R package | http://www.ams.sunysb.edu/∼pfkuan/softwares.html#methylDMV | 27896998 |
| WFMM[ 176 ] | Identification of differentially methylated loci | 2016 | Software | https://biostatistics.mdanderson.org/SoftwareDownload | 26559505 |
| MethylAction[ 177 ] | Detection of differentially methylated regions | 2016 | R package | http://jeffbhasin.github.io/methylaction | 26673711 |
| AmpliMethProfiler[ 178 ] | Identification of methylated/unmethylated regions | 2016 | Python package | http://amplimethprofiler.sourceforge.net | 27884103 |
| iDNA‐Methyl[ 179 ] | Identification of differentially methylated loci | 2015 | Webserver | http://www.jci‐bioinfo.cn/iDNA‐Methyl | 25596338 |
| swDMR[ 180 ] | Detection of differentially methylated regions | 2015 | Software | http://sourceforge.net/projects/swDMR | 26176536 |
| EpiDiff[ 181 ] | Identification of differential epigenetic modification regions | 2013 | Software | http://bioinfo.hrbmu.edu.cn/epidiff | 24109772 |
| Analysis of the association between epigenetic variation and disease/phenotype | |||||
| EWAS2.0[ 182 ] | Analysis of the association between epigenetic variation and disease/phenotype | 2018 | Software | http://www.ewas.org.cn | 29566144 |
| EWAS1.0[ 183 ] | Analysis of the association between epigenetic variation and disease/phenotype | 2016 | Software | http://www.ewas.org.cn | 27892496 |
| DEMGD[ 184 ] | Extraction of associations of methylated genes and diseases | 2013 | Webserver | http://www.cbrc.kaust.edu.sa/demgd | 24147091 |
| Comprehensive Analysis of DNA Methylation Data | |||||
| GLINT[ 185 ] | Analysis of high‐throughput DNA‐methylation array data | 2017 | Python package | https://github.com/cozygene/glint/releases | 28177067 |
| TABSAT[ 186 ] | Analysing targeted bisulfite sequencing data | 2016 | Software | http://demo.platomics.com | 27467908 |
| BioVLAB‐mCpG‐SNP‐EXPRESS[ 187 ] | Various integrated analyses such as methylation vs. gene expression and mutation vs methylation are performed | 2016 | Webserver | http://biohealth.snu.ac.kr/software/biovlab_mcpg_snp_express | 27477210 |
| RefFreeDMA[ 188 ] | Differential DNA methylation analysis | 2015 | Software | http://RefFreeDMA.computational‐epigenetics.org | 26673328 |
| MethGo[ 189 ] | Analyzing whole‐genome bisulfite sequencing data | 2015 | Python package | http://paoyangchen‐laboratory.github.io/methgo | 26680022 |
| MethylSig[ 190 ] | DNA methylation analysis | 2014 | R package | http://sartorlab.ccmb.med.umich.edu/software | 24836530 |
| Methy‐pipe[ 191 ] | Whole genome bisulfite sequencing data analysis | 2014 | Software | http://sunlab.lihs.cuhk.edu.hk/methy‐pipe | 24945300 |
| RnBeads[ 192 ] | DNA methylation analysis | 2014 | Software | http://rnbeads.mpi‐inf.mpg.de | 25262207 |
| APEG[ 193 ] | Analyze the functions of epigenomic modifications | 2013 | Software | http://systemsbio.ucsd.edu/apeg | 24339764 |
| GBSA[ 194 ] | Analysing whole genome bisulfite sequencing data | 2013 | Python package | http://ctrad‐csi.nus.edu.sg/gbsa | 23268441 |
| EpiExplorer[ 195 ] | Analysis of large epigenomic datasets | 2012 | Software | http://epiexplorer.mpi‐inf.mpg.de | 23034089 |
| IMA [196] | Analysis of Illumina 450K | 2012 | R package | http://www.rforge.net/IMA | 22253290 |
| BiQ analyzer HT[ 197 ] | Locus‐specific analysis of DNA methylation by high‐throughput bisulfite sequencing | 2011 | Software | http://biq‐analyzer‐ht.bioinf.mpi‐inf.mpg.de | 21565797 |
| CNAmet[ 198 ] | Comprehensive analysis of high‐throughput copy number, DNA methylation and gene expression data | 2011 | R package | http://csbi.ltdk.helsinki.fi/CNAmet | 21228048 |
| Methyl‐analyzer[ 199 ] | DNA methylation analysis | 2011 | Python package | http://github.com/epigenomics/methylmaps | 21685051 |
| Prediction of histone modifications and DNA methylation level | |||||
| Pancancer DNA Methylation Trackhub[ 200 ] | Depicting the overall DNA methylation status | 2018 | Webserver | http://maplab.cat/tcga_450k_trackhub | 29605850 |
| LR450K [201] | Prediction of methylation levels | 2016 | R package | http://wanglab.ucsd.edu/star/LR450K | 26883487 |
| Epigram[ 202 ] | Predicts histone modification and DNA methylation patterns from DNA motifs | 2015 | Software | http://wanglab.ucsd.edu/star/epigram | 25240437 |
| MLML[ 203 ] | Estimates of DNA methylation and hydroxymethylation levels | 2013 | Software | http://smithlab.usc.edu/software/mlml | 23969133 |
| DMEAS[ 204 ] | Estimates methylation levels | 2013 | Software | http://sourceforge.net/projects/dmeas/files | 23749987 |
| Prediction of complex traits | |||||
| TANDEM[ 205 ] | Measure drug response | 2016 | R package | http://ccb.nki.nl/software/tandem | 27587657 |
| OmicKriging[ 206 ] | Prediction of complex traits, such as disease risk or drug response | 2014 | R package | http://www.scandb.org/newinterface/tools/OmicKriging.html | 24799323 |
| ITFoM[ 207 ] | Prediction of health risks, progression of diseases, and selection and efficacy of treatments | 2013 | Webserver | http://www.itfom.eu | 23165094 |
| Identification of differential cell types | |||||
| BPRMeth [208] | Predicting gene expression levels or clustering genomic regions or cells | 2018 | R package | http://bioconductor.org/packages/BPRMeth | 29522078 |
| CellDMC[ 209 ] | Identification of differentially methylated cell types | 2018 | R package | https://github.com/sjczheng/EpiDISH | 30504870 |
| eFORGE[ 210 ] | Identifying cell type‐specific signal | 2016 | Webserver | http://eforge.cs.ucl.ac.uk | 27851974 |
| Methylation data processing and normalization | |||||
| OmicsPrint[ 211 ] | Detection of data linkage errors in multiple omics studies | 2018 | R package | http://bioconductor.org/packages/omicsPrint | 29420690 |
| FuntooNorm[ 212 ] | Normalization of DNA methylation data | 2016 | R package | https://github.com/GreenwoodLab/funtooNorm | 26500152 |
| Beclear[ 213 ] | Correction of batch effects in DNA methylation data | 2016 | R package | http://bioconductor.org/packages/release/bioc/html/BEclear.html | 27559732 |
| Jllumina[ 214 ] | Handling of 450 k and EPIC data | 2016 | Java package | http://dimmer.compbio.sdu.dk/download.html | 28187410 |
| SMETHILLIUM[ 215 ] | Spatial normalization method for Illumina infinium HumanMethylation BeadChip | 2011 | R package | http://bioinfo.curie.fr/projects/smethillium | 21493659 |