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Rohit Kumar Verma, Vibhor Kumar
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Disease prediction by cell-free DNA methylation
10.1093/bib/bby029 · 2019
Finding new cancer epigenetic and genetic biomarkers from cell-free DNA by combining SALP-seq and machine learning: Esophageal cancer as an example
10.1101/2020.01.18.911172 · 2020
Techniques of using circulating tumor DNA as a liquid biopsy component in cancer management, Computational and Structural
2018
Comprehensive human cell-type methylation atlas reveals origins of circulating cell-free DNA in health and disease
10.1038/s41467-018-07466-6 · 2018
10.1039/c9an00935c
10.1039/c9an00935c
10.3390/cancers11060805
10.3390/cancers11060805
Methods for genome-wide DNA methylation analysis in human cancer
10.1093/bfgp/elw010 · 2016
Methylation of cell-free circulating DNA in the diagnosis of cancer
10.3389/fmolb.2015.00013 · 2015
Cell-Free DNA: Hope and Potential Application in Cancer
2021
Grail and the quest for earlier multi-cancer detection
2018
10.3390/cancers11111741
10.3390/cancers11111741
10.1111/brv.12413
10.1111/brv.12413
10.3390/ijms21218062
10.3390/ijms21218062
Characterization of Cell Free Plasma Methyl-DNA From Xenografted Tumors to Guide the Selection of Diagnostic Markers for Early-Stage Cancers
2021
10.3390/cancers13040728
10.3390/cancers13040728
10.1093/bioinformatics/btaa999
10.1093/bioinformatics/btaa999
10.1016/j.bdq.2019.100087
10.1016/j.bdq.2019.100087
Kinetics of circulating cell-free DNA for biomedical applications: Critical appraisal of the literature
10.4155/fsoa-2017-0140 · 2018
10.3390/biom10121677
10.3390/biom10121677
DNA methylation data by sequencing: Experimental approaches and recommendations for tools and pipelines for data analysis
10.1186/s13148-019-0795-x · 2019
DNA Analysis by Restriction Enzyme (DARE) enables concurrent genomic and epigenomic characterization of single cells
10.1093/nar/gkz717 · 2019
Absolute quantification of DNA methylation using microfluidic chip-based digital PCR
10.1016/j.bios.2017.05.021 · 2017
10.1038/s41598-018-19655-w
10.1038/s41598-018-19655-w
Circulating cell-free DNA from plasma undergoes less fragmentation during bisulfite treatment than genomic DNA due to low molecular weight
10.1371/journal.pone.0224338 · 2019
10.1007/978-1-4939-7774-1_17
10.1007/978-1-4939-7774-1_17
10.1016/j.canlet.2012.10.040
10.1016/j.canlet.2012.10.040
10.1101/gr.232587.117
10.1101/gr.232587.117
10.1016/j.gde.2017.01.017
10.1016/j.gde.2017.01.017
10.1038/cr.2015.126
10.1038/cr.2015.126
Detection of Colorectal Cancer in Circulating Cell-Free DNA by Methylated CpG Tandem Amplification and Sequencing
10.1373/clinchem.2019.301804 · 2019
10.1111/nph.15388
10.1111/nph.15388
cfNOMe —A single assay for comprehensive epigenetic analyses of cell-free DNA
10.1186/s13073-020-00750-5 · 2020
Enrichment methods provide a feasible approach to comprehensive and adequately powered investigations of the brain methylome
2017
Fetal-specific DNA methylation ratio permits noninvasive prenatal diagnosis of trisomy 21
10.1038/nm.2312 · 2011
Preparation of cfMeDIP-seq libraries for methylome profiling of plasma cell-free DNA
10.1038/s41596-019-0202-2 · 2019
10.1038/nprot.2012.012
10.1038/nprot.2012.012
Comparison of methyl-DNA immunoprecipitation (MeDIP) and methyl-CpG binding domain (MBD) protein capture for genome-wide DNA methylation analysis reveal CpG sequence coverage bias
10.4161/epi.6.1.13313 · 2011
A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis
10.1038/nbt1414 · 2008
Computational analysis of genome-wide DNA methylation during the differentiation of human embryonic stem cells along the endodermal lineage
10.1101/gr.110114.110 · 2010
10.1126/science.1170116
10.1126/science.1170116
10.1093/nar/gku457
10.1093/nar/gku457 · doi-reference
10.1007/s40484-019-0183-8
10.1007/s40484-019-0183-8 · doi-reference
10.1093/bioinformatics/btu339
10.1093/bioinformatics/btu339 · doi-reference
methylKit: A comprehensive R package for the analysis of genome-wide DNA methylation profiles
10.1186/gb-2012-13-10-r87 · doi-reference
De novo identification of differentially methylated regions in the human genome
10.1186/1756-8935-8-6 · doi-reference
RnBeads 2.0: Comprehensive analysis of DNA methylation data
10.1186/s13059-019-1664-9 · doi-reference
MethylAction: Detecting differentially methylated regions that distinguish biological subtypes
10.1093/nar/gkv1461 · doi-reference
10.5772/61207
10.5772/61207 · doi-reference
Resources for methylome analysis suitable for gene knockout studies of potential epigenome modifiers
10.1186/2047-217x-1-3 · doi-reference
MEDME: An experimental and analytical methodology for the estimation of DNA methylation levels based on microarray derived MeDIP-enrichment
10.1101/gr.080721.108 · doi-reference
Msuite: A High-Performance and Versatile DNA Methylation Data-Analysis Toolkit
10.1016/j.patter.2020.100127 · doi-reference
A mostly traditional approach improves alignment of bisulfite-converted DNA
10.1093/nar/gks275 · doi-reference
The GEM mapper: Fast, accurate and versatile alignment by filtration
10.1038/nmeth.2221 · doi-reference
10.1145/2382936.2382938
10.1145/2382936.2382938 · doi-reference
BRAT-BW: Efficient and accurate mapping of bisulfite-treated reads
10.1093/bioinformatics/bts264 · doi-reference
10.1093/bioinformatics/btq057
10.1093/bioinformatics/btq057 · doi-reference
Fast Mapping of Short Sequences with Mismatches, Insertions and Deletions Using Index Structures
10.1371/journal.pcbi.1000502 · doi-reference
MethylCoder: Software pipeline for bisulfite-treated sequences
10.1093/bioinformatics/btr394 · doi-reference
BSmooth: From whole genome bisulfite sequencing reads to differentially methylated regions
10.1186/gb-2012-13-10-r83 · doi-reference
10.1186/1471-2164-14-774
10.1186/1471-2164-14-774 · doi-reference
10.1093/bioinformatics/btr167
10.1093/bioinformatics/btr167 · doi-reference
10.1186/1471-2105-10-232
10.1186/1471-2105-10-232 · doi-reference
An integrated package for bisulfite DNA methylation data analysis with Indel-sensitive mapping
10.1186/s12859-018-2593-4 · doi-reference
10.1609/aaai.v24i1.7682
10.1609/aaai.v24i1.7682 · doi-reference
10.1016/j.annonc.2020.02.011
10.1016/j.annonc.2020.02.011 · doi-reference
Circulating cell-free DNA in breast cancer: Size profiling, levels, and methylation patterns lead to prognostic and predictive classifiers
10.1038/s41388-018-0660-y · doi-reference
10.1126/scitranslmed.aax7533
10.1126/scitranslmed.aax7533 · doi-reference
10.1186/s12885-019-6003-8
10.1186/s12885-019-6003-8 · doi-reference
10.1038/s41586-018-0703-0
10.1038/s41586-018-0703-0 · doi-reference
10.1371/journal.pgen.0030161
10.1371/journal.pgen.0030161 · doi-reference
Sparse PCA corrects for cell type heterogeneity in epigenome-wide association studies
10.1038/nmeth.3809 · doi-reference
Epigenome-wide association studies without the need for cell-type composition
10.1038/nmeth.2815 · doi-reference
10.1093/bioinformatics/btu029
10.1093/bioinformatics/btu029 · doi-reference
TOAST: Improving reference-free cell composition estimation by cross-cell type differential analysis
10.1186/s13059-019-1778-0 · doi-reference
CDSeq: A novel complete deconvolution method for dissecting heterogeneous samples using gene expression data
10.1371/journal.pcbi.1007510 · doi-reference
Cell Mix: A comprehensive toolbox for gene expression deconvolution
10.1093/bioinformatics/btt351 · doi-reference
10.1038/nmeth.3337
10.1038/nmeth.3337 · doi-reference
10.1186/s12859-017-1511-5
10.1186/s12859-017-1511-5 · doi-reference
10.2217/epi-2016-0153
10.2217/epi-2016-0153 · doi-reference
10.1093/hmg/ddx275
10.1093/hmg/ddx275 · doi-reference