Statistical modeling for selecting housekeeper genes

被引：152

作者：

Szabo, A ^{[1
]}

Perou, CM

Karaca, M

Perreard, L

Quackenbush, JF

Bernard, PS

机构：

[1] Huntsman Canc Inst, Dept Oncol Sci, Salt Lake City, UT 84112 USA

[2] Univ N Carolina, Lineberger Comprehens Canc Ctr, Chapel Hill, NC 27599 USA

[3] Univ N Carolina, Dept Genet, Chapel Hill, NC 27599 USA

[4] ARUP Labs Inc, Salt Lake City, UT 84108 USA

[5] Univ Utah, Dept Pathol, Salt Lake City, UT 84112 USA

来源：

GENOME BIOLOGY | 2004年 / 5卷 / 08期

关键词：

D O I：

10.1186/gb-2004-5-8-r59

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

There is a need for statistical methods to identify genes that have minimal variation in expression across a variety of experimental conditions. These 'housekeeper' genes are widely employed as controls for quantification of test genes using gel analysis and real-time RT-PCR. Using real-time quantitative RT-PCR, we analyzed 80 primary breast tumors for variation in expression of six putative housekeeper genes (MRPL19 (mitochondrial ribosomal protein L19), PSMC4 (proteasome (prosome, macropain) 26S subunit, ATPase, 4), SF3A1 (splicing factor 3a, subunit 1, 120 kDa), PUM1 (pumilio homolog 1 (Drosophila)), ACTB (actin, beta) and GAPD (glyceraldehyde-3-phosphate dehydrogenase)). We present appropriate models for selecting the best housekeepers to normalize quantitative data within a given tissue type (for example, breast cancer) and across different types of tissue samples.

引用

页数：10

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