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Rat toxicogenomic study reveals analytical consistency across microarray platforms

delete2006-09-08
delete367
PRE
AI
L
Lei Guo *
E
Edward K. Lobenhofer
C
Charles Wang
R
Richard Shippy
S
Stephen Harris
张璐 (Lu Zhang)
N
Nan Mei
陈涛 cover
陈涛 (Tao Chen)
D
Damir Herman
F
Federico Goodsaid
P
Patrick Hurban
K
Kenneth L. Phillips
J
Jun Xu
X
Xutao Deng
Y
Yongming Sun
W
Weida Tong
Y
Yvonne P. Dragan
L
Leming Shi
DOI:10.1038/nbt1238delete
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Abstract

Abstract

En 中文
To validate and extend the findings of the MicroArray Quality Control (MAQC) project, a biologically relevant toxicogenomics data set was generated using 36 RNA samples from rats treated with three chemicals (aristolochic acid, riddelliine and comfrey) and each sample was hybridized to four microarray platforms. The MAQC project assessed concordance in intersite and cross-platform comparisons and the impact of gene selection methods on the reproducibility of profiling data in terms of differentially expressed genes using distinct reference RNA samples. The real-world toxicogenomic data set reported here showed high concordance in intersite and cross-platform comparisons. Further, gene lists generated by fold-change ranking were more reproducible than those obtained by t-test P value or Significance Analysis of Microarrays. Finally, gene lists generated by fold-change ranking with a nonstringent P-value cutoff showed increased consistency in Gene Ontology terms and pathways, and hence the biological impact of chemical exposure could be reliably deduced from all platforms analyzed.
Keywords:
PYRROLIZIDINE SENECIO ALKALOIDS
BIG BLUE RATS
GENE-EXPRESSION
ARISTOLOCHIC ACID
VITAMIN-A
COPPER
METABOLISM
LIVER
MUTAGENICITY
RIDDELLIINE
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Journal

Nature Biotechnology cover
Nature Biotechnology
IF:
41.7
Papers:
1.2W
Citations:
10.1W

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