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svaseq: removing batch effects and other unwanted noise from sequencing data

bioRxiv

Jun 25, 2014

Jeffrey T Leek

Abstract

It is now well known that unwanted noise and unmodeled artifacts such as batch effects can dramatically reduce the accuracy of statistical inference in genomic experiments. We introduced surrogate variable analysis for estimating these artifacts by (1) identifying the part of the genomi...read more

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Sequencing
Research Study
Cloning Vectors
Genomics
Analysis
Extracellular Matrix
Genetic Vectors
Genome
Nucleic Acid Sequencing
30
1
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svaseq: removing batch effects and other unwanted noise from sequencing data

bioRxiv

Jun 25, 2014

Jeffrey T Leek

PMID: 990006585

DOI: 10.1101/006585

Abstract

It is now well known that unwanted noise and unmodeled artifacts such as batch effects can dramatically reduce the accuracy of statistical inference in genomic experiments. We introduced surrogate variable analysis for estimating these artifacts by (1) identifying the part of the genomi...read more

Mentioned in this Paper

Sequencing
Research Study
Cloning Vectors
Genomics
Analysis
Extracellular Matrix
Genetic Vectors
Genome
Nucleic Acid Sequencing
30
1
Paper Details
References
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  • Citations
  • finger pointing at paper

    References currently unavailable

    We're still populating references for this paper, please check back later.
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