Difference between revisions of "Literature Studies"
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|- 1999 || Perkins DN || [[Probability-based protein identification by searching sequence databases using mass spectrometry data]] | |- 1999 || Perkins DN || [[Probability-based protein identification by searching sequence databases using mass spectrometry data]] | ||
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− | | 2003 || || [[A comparison of normalization methods for high density oligonucleotide array data based on variance and bias]] | + | | 2003 || Bolstad || [[A comparison of normalization methods for high density oligonucleotide array data based on variance and bias]] |
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− | | 2003 || || [[Preprocessing of tandem mass spectrometric data to support automatic protein identification]] | + | | 2003 || Gentzel || [[Preprocessing of tandem mass spectrometric data to support automatic protein identification]] |
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− | | 2005 || || [[Comparison of Affymetrix GeneChip Expression Measures]] | + | | 2005 || Irizarry || [[Comparison of Affymetrix GeneChip Expression Measures]] |
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| 2005 || Meleth S || [[The case for well-conducted experiments to validate statistical protocols for 2D gels: different pre-processing = different lists of significant proteins]] | | 2005 || Meleth S || [[The case for well-conducted experiments to validate statistical protocols for 2D gels: different pre-processing = different lists of significant proteins]] | ||
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− | | 2005 || || [[Comparison of background correction and normalization procedures for high-density oligonucleotide microarrays]] | + | | 2005 || Freudenberg || [[Comparison of background correction and normalization procedures for high-density oligonucleotide microarrays]] |
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− | | 2006 || || [[Using RNA sample titrations to assess microarray platform performance and normalization techniques]] | + | | 2006 || Shippy || [[Using RNA sample titrations to assess microarray platform performance and normalization techniques]] |
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| 2006 || Wang P || [[Normalization regarding non-random missing values in high-throughput mass spectrometry data]] | | 2006 || Wang P || [[Normalization regarding non-random missing values in high-throughput mass spectrometry data]] | ||
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| 2007 || Cannataro M || [[MS‐Analyzer: preprocessing and data mining services for proteomics applications on the Grid]] | | 2007 || Cannataro M || [[MS‐Analyzer: preprocessing and data mining services for proteomics applications on the Grid]] | ||
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− | | 2008 || || [[Comparison of preprocessing methods for the hgU133+2 chip from Affymetrix]] | + | | 2008 || Goebels || [[Comparison of preprocessing methods for the hgU133+2 chip from Affymetrix]] |
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− | | 2009 || || [[Comparison of Affymetrix data normalization methods using 6,926 experiments across five array generations]] | + | | 2009 || Autio || [[Comparison of Affymetrix data normalization methods using 6,926 experiments across five array generations]] |
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| 2009 || Mar JC || [[Data-driven normalization strategies for high-throughput quantitative RT-PCR]] | | 2009 || Mar JC || [[Data-driven normalization strategies for high-throughput quantitative RT-PCR]] | ||
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| 2009 || Vakhrushev SY || [[Software platform for high-throughput glycomics]] | | 2009 || Vakhrushev SY || [[Software platform for high-throughput glycomics]] | ||
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− | | 2010 || || [[Consistency of predictive signature genes and classifiers generated using different microarray platforms]] | + | | 2010 || Fan || [[Consistency of predictive signature genes and classifiers generated using different microarray platforms]] |
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− | | 2010 || || [[Detecting and correcting systematic variation in large-scale RNA sequencing data]] | + | | 2010 || Li || [[Detecting and correcting systematic variation in large-scale RNA sequencing data]] |
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− | | 2010 || || [[Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments]] | + | | 2010 || Bullard || [[Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments]] |
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− | | 2010 || || [[Normalization of RNA-seq data using factor analysis of control genes or samples]] | + | | 2010 || Risso || [[Normalization of RNA-seq data using factor analysis of control genes or samples]] |
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| 2010 || Armananzas R || [[Peakbin selection in mass spectrometry data using a consensus approach with estimation of distribution algorithms]] | | 2010 || Armananzas R || [[Peakbin selection in mass spectrometry data using a consensus approach with estimation of distribution algorithms]] | ||
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− | | 2011 || || [[Affymetrix GeneChip microarray preprocessing for multivariate analyses]] | + | | 2011 || McCall || [[Affymetrix GeneChip microarray preprocessing for multivariate analyses]] |
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| 2011 || Zhang ZM || [[Peak alignment using wavelet pattern matching and differential evolution]] | | 2011 || Zhang ZM || [[Peak alignment using wavelet pattern matching and differential evolution]] | ||
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− | | 2012 || || [[A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis]] | + | | 2012 || Dillies || [[A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis]] |
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| 2013 || García-Torres M || [[Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data]] | | 2013 || García-Torres M || [[Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data]] | ||
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| 2013 || Horvatovich P || [[Bioinformatics and Statistics: LC‐MS (/MS) Data Preprocessing for Biomarker Discovery]] | | 2013 || Horvatovich P || [[Bioinformatics and Statistics: LC‐MS (/MS) Data Preprocessing for Biomarker Discovery]] | ||
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− | | 2014 || || [[Normalyzer: A Tool for Rapid Evaluation of Normalization Methods for Omics Data Sets]] | + | | 2014 || Chawade || [[Normalyzer: A Tool for Rapid Evaluation of Normalization Methods for Omics Data Sets]] |
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| 2014 || Zhou X || [[Prevention, diagnosis and treatment of high-throughput sequencing data pathologies]] | | 2014 || Zhou X || [[Prevention, diagnosis and treatment of high-throughput sequencing data pathologies]] |
Revision as of 16:16, 28 February 2020
Page summary |
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Here outcomes of benchmarking studies from the literature are collected. The primary aim is a comprehensive overview about neutral benchmark studies, i.e. assessments which were performed independenty on publication of a new approach. Studies which are not neutral are put in brackets. 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. |
Contents
1 Results from Literature
1.1 Classification
Year | First Author | Title |
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2003 | Wu | Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data |
2005 | Harper | A review and comparison of classification algorithms for medical decision making |
2005 | Bellaachia | Predicting Breast Cancer Survivability Using Data Mining Techniques |
1.2 Selection of Differential Features and Regions
1.2.1 Identifying differential features
1.2.2 Identifying differential regions (e.g. DMRs)
1.2.3 Identifying sets of features (e.g. gene set analyses)
Year | First Author | Title |
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2009 | Ackermann | A general modular framework for gene set enrichment analysis |
2009 | Tintle | Comparing gene set analysis methods on single-nucleotide polymorphism data from Genetic Analysis Workshop 16 |
2018 | Mathur | Gene set analysis methods: a systematic comparison |
2020 | Geistlinger | Toward a gold standard for benchmarking gene set enrichment analysis |
1.2.4 Dimension reduction
Year | First Author | Title |
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2008 | Janecek | On the Relationship Between Feature Selection and Classification Accuracy |
2015 | Fernández-Gutiérrez | Comparing feature selection methods for highdimensional imbalanced data: identifying rheumatoid arthritis cohorts from routine data |