Filtering data from high-throughput experiments based on measurement reliability.

Proceedings of the National Academy of Sciences of the United States of America ·Vol. 107 ·No. 46 ·2010-11-16 ·Pages E173-4; author reply E175

Talloen W, Hochreiter S, Bijnens L, Kasim A, Shkedy Z, Amaratunga D, Göhlmann H

Abstract

暂无摘要

MeSH Terms

Cell Line, Tumor High-Throughput Screening Assays/methods Humans Models, Biological Reproducibility of Results Software Statistics as Topic

Authors & Affiliations

7 authors, click to expand affiliations / ORCID

Talloen Willem

Hochreiter Sepp

Bijnens Luc

Kasim Adetayo

Shkedy Ziv

Amaratunga Dhammika

Göhlmann Hinrich

References (2)

2 references, click to expand

I/NI-calls for the exclusion of non-informative genes: a highly effective filtering tool for microarray data.
Bioinformatics. 2007 Nov 1;23(21):2897-902 PMID: 17921172
Independent filtering increases detection power for high-throughput experiments.
Proc Natl Acad Sci U S A. 2010 May 25;107(21):9546-51 PMID: 20460310

Article Info

Journal

Proceedings of the National Academy of Sciences of the United States of America

Abbr.

Proc Natl Acad Sci U S A

ISSN

1091-6490

DOI

10.1073/pnas.1010604107

Published

2010-11-16

Epub

2010-00-08

Pages

E173-4; author reply E175

Language

English

Region

United States

NLM ID

7505876

PMCID

PMC2993399

Subset

Corrections

CommentOn

PMID: 20460310

External Links

PubMed source DOI: 10.1073/pnas.1010604107 PMC Full Text View journal details

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Filtering data from high-throughput experiments based on measurement reliability.

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