Difference between revisions of "Literature Studies"

(Feature Selection)
(Thee papers found at bioRxiv)
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''' 2014 '''</br>
 
''' 2014 '''</br>
 
* [[Normalyzer: A Tool for Rapid Evaluation of Normalization Methods for Omics Data Sets]]
 
* [[Normalyzer: A Tool for Rapid Evaluation of Normalization Methods for Omics Data Sets]]
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 +
=== Analysis workflows and pipelines ===
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''' 2015 '''</br>
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* [[ComparingVariant Call Files for Performance Benchmarkingof Next-Generation Sequencing Variant Calling Pipelines]]
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''' 2017 '''</br>
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* [[A benchmarking of workflows for detecting differential splicing and differential expression at isoform level in human RNA-seq studies]]
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''' 2019 '''</br>
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* [[A Systematic Evaluation of Single CellRNA-Seq Analysis Pipelines]]
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* [[Benchmarking workflows to assess performance and suitability of germline variant calling pipelines in clinical diagnostic assays]]

Revision as of 11:41, 22 May 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 Selection of Differential Features and Regions

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

1.7 Analysis workflows and pipelines

2015

2017

2019