Difference between revisions of "Literature Studies"

(Identifying differential regions (e.g. DMRs))
(Identifying differential regions (e.g. DMRs))
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* [[Defiant: (DMRs: easy, fast, identification and ANnoTation) identifies differentially Methylated regions from iron-deficient rat hippocampus]]
 
* [[Defiant: (DMRs: easy, fast, identification and ANnoTation) identifies differentially Methylated regions from iron-deficient rat hippocampus]]
 
* [[DMRcaller: a versatile R/Bioconductor package for detection and visualization of differentially methylated regions in CpG and non-CpG contexts]]
 
* [[DMRcaller: a versatile R/Bioconductor package for detection and visualization of differentially methylated regions in CpG and non-CpG contexts]]
* [[mCSEA: Detecting subtle differentially methylated regions]]
 
 
* [[MethCP: Differentially Methylated Region Detection with Change Point Models (bioRxiv)]]
 
* [[MethCP: Differentially Methylated Region Detection with Change Point Models (bioRxiv)]]
  

Revision as of 15:01, 14 February 2019

Page summary
Here outcomes of benchmarking studies from the literature are collected.

The focus is on computational methods for analyzing experimental data (instead of comparing experimental techniques or platforms).

Please extend this list by creating a new page and adding a link below.
Use the guidelines described here.

1 Results from Literature

1.1 Classification

2003

2005

2016

1.2 Feature Selection

1.2.1 Identifying differential features

2006

2010

2017

2018

1.2.2 Identifying differential regions (e.g. DMRs)

2015

2016

2017

2018

1.2.3 Identifying sets of features (e.g. gene set analyses)

1.2.4 Dimension reduction

2008

2015


1.3 Imputation methods for missing values

2001

2015

2018


1.4 ODE-based Modelling

2001

2008

2013

2018


1.5 Omics Workflows

2017


1.6 Preprocessing high-throughput data

2003

2005

2006

2008

2009

2010

2011

2012

2014