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Statistical modeling for selecting housekeeper genes. Genome Biol 2004;5(8):R59 PMID: 15287981 PMCID: PMC507884

Pubmed ID

15287981

Abstract

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.

Author List

Szabo A, Perou CM, Karaca M, Perreard L, Palais R, Quackenbush JF, Bernard PS

Author

Aniko Szabo PhD Associate Professor in the Institute for Health and Equity department at Medical College of Wisconsin




Scopus

2-s2.0-15444373286   149 Citations

MESH terms used to index this publication - Major topics in bold

ATPases Associated with Diverse Cellular Activities
Adenosine Triphosphatases
Algorithms
Breast
Breast Neoplasms
Cell Line, Tumor
DNA, Complementary
DNA-Binding Proteins
Gene Dosage
Gene Expression
Gene Expression Profiling
Genes, Essential
Humans
Mitochondrial Proteins
Models, Genetic
Oligonucleotide Array Sequence Analysis
Proteasome Endopeptidase Complex
RNA Splicing Factors
RNA, Messenger
RNA-Binding Proteins
Reference Standards
Reverse Transcriptase Polymerase Chain Reaction
Ribonucleoprotein, U2 Small Nuclear
Ribosomal Proteins
Transcription Factors
jenkins-FCD Prod-299 9ef562391eceb2b8f95265c767fbba1ce5a52fd6