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.
INRA, UR337, Jouy-en-Josas, France (INRA_J). florence.jaffrezic@jouy.inra.fr
Florence
F
Jaffrézic
Dirk-Jan
DJ
de Koning
Paul J
PJ
Boettcher
Agnès
A
Bonnet
Bart
B
Buitenhuis
Rodrigue
R
Closset
Sébastien
S
Déjean
Céline
C
Delmas
Johanne C
JC
Detilleux
Peter
P
Dovc
Mylène
M
Duval
Jean-Louis
JL
Foulley
Jakob
J
Hedegaard
Henrik
H
Hornshøj
Ina
I
Hulsegge
Luc
L
Janss
Kirsty
K
Jensen
Li
L
Jiang
Miha
M
Lavric
Kim-Anh
KA
Lê Cao
Mogens Sandø
MS
Lund
Roberto
R
Malinverni
Guillemette
G
Marot
Haisheng
H
Nie
Wolfram
W
Petzl
Marco H
MH
Pool
Christèle
C
Robert-Granié
Magali
M
San Cristobal
Evert M
EM
van Schothorst
Hans-Joachim
HJ
Schuberth
Peter
P
Sørensen
Alessandra
A
Stella
Gwenola
G
Tosser-Klopp
David
D
Waddington
Michael
M
Watson
Wei
W
Yang
Holm
H
Zerbe
Hans-Martin
HM
Seyfert
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