Analysis of the real EADGENE data set: comparison of methods and guidelines for data normalisation and selection of differentially expressed genes (open access publication).
A large variety of methods has been proposed in the literature for microarray data analysis. The aim of this paper was to present techniques used by the EADGENE (European Animal Disease Genomics Network of Excellence) WP1.4 participants for data quality control, normalisation and statistical methods for the detection of differentially expressed genes in order to provide some more general data analysis guidelines. All the workshop participants were given a real data set obtained in an EADGENE funded microarray study looking at the gene expression changes following artificial infection with two different mastitis causing bacteria: Escherichia coli and Staphylococcus aureus. It was reassuring to see that most of the teams found the same main biological results. In fact, most of the differentially expressed genes were found for infection by E. coli between uninfected and 24 h challenged udder quarters. Very little transcriptional variation was observed for the bacteria S. aureus. Lists of differentially expressed genes found by the different research teams were, however, quite dependent on the method used, especially concerning the data quality control step. These analyses also emphasised a biological problem of cross-talk between infected and uninfected quarters which will have to be dealt with for further microarray studies.
Jaffrézic
Florence
F
INRA, UR337, Jouy-en-Josas, France (INRA_J). florence.jaffrezic@jouy.inra.fr
de Koning
Dirk-Jan
DJ
Boettcher
Paul J
PJ
Bonnet
Agnès
A
Buitenhuis
Bart
B
Closset
Rodrigue
R
Déjean
Sébastien
S
Delmas
Céline
C
Detilleux
Johanne C
JC
Dovc
Peter
P
Duval
Mylène
M
Foulley
Jean-Louis
JL
Hedegaard
Jakob
J
Hornshøj
Henrik
H
Hulsegge
Ina
I
Janss
Luc
L
Jensen
Kirsty
K
Jiang
Li
L
Lavric
Miha
M
Lê Cao
Kim-Anh
KA
Lund
Mogens Sandø
MS
Malinverni
Roberto
R
Marot
Guillemette
G
Nie
Haisheng
H
Petzl
Wolfram
W
Pool
Marco H
MH
Robert-Granié
Christèle
C
San Cristobal
Magali
M
van Schothorst
Evert M
EM
Schuberth
Hans-Joachim
HJ
Sørensen
Peter
P
Stella
Alessandra
A
Tosser-Klopp
Gwenola
G
Waddington
David
D
Watson
Michael
M
Yang
Wei
W
Zerbe
Holm
H
Seyfert
Hans-Martin
HM
D000704:Analysis of Variance; D000818:Animals; D000829:Animals, Domestic / Q000235:genetics; D015982:Bias; D002417:Cattle / Q000235:genetics; D003627:Data Interpretation, Statistical; D030541:Databases, Genetic; D004927:Escherichia coli Infections / Q000235:genetics / Q000662:veterinary; D005060:Europe; D005260:Female; D020869:Gene Expression Profiling / Q000592:standards / Q000706:statistics & numerical data*; D017408:Guidelines as Topic; D008414:Mastitis, Bovine / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis / Q000592:standards / Q000706:statistics & numerical data*; D011786:Quality Control; D012984:Software; D013203:Staphylococcal Infections / Q000235:genetics / Q000662:veterinary