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基因表达测量:稳健数据分析的方差建模考虑因素。

Gene-expression measurement: variance-modeling considerations for robust data analysis.

机构信息

Department of Bioengineering, University of California at San Diego, La Jolla, California, USA.

出版信息

Nat Immunol. 2012 Feb 16;13(3):199-203. doi: 10.1038/ni.2244.

DOI:10.1038/ni.2244
PMID:22344273
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4358796/
Abstract

System-wide measurements of gene expression by DNA microarray and, more recently, RNA-sequencing strategies have become de facto tools of modern biology and have led to deep understanding of biological mechanisms and pathways. However, analyses of the measurements have often ignored statistically robust methods that account for variance, resulting in misleading biological interpretations.

摘要

通过 DNA 微阵列和最近的 RNA 测序策略进行全系统的基因表达测量已成为现代生物学的事实上的工具,并深入了解了生物学机制和途径。然而,这些测量的分析往往忽略了统计上稳健的方法,这些方法考虑了方差,从而导致了误导性的生物学解释。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9fb/4358796/5ef1f9331cbf/nihms632472f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9fb/4358796/1955930d8d26/nihms632472f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9fb/4358796/e26f239eb852/nihms632472f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9fb/4358796/5995f4fbb11f/nihms632472f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9fb/4358796/5ef1f9331cbf/nihms632472f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9fb/4358796/1955930d8d26/nihms632472f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9fb/4358796/e26f239eb852/nihms632472f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9fb/4358796/5995f4fbb11f/nihms632472f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9fb/4358796/5ef1f9331cbf/nihms632472f4.jpg

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PLoS One. 2010 Sep 3;5(9):e12336. doi: 10.1371/journal.pone.0012336.
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Preferred analysis methods for Affymetrix GeneChips. II. An expanded, balanced, wholly-defined spike-in dataset.
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