Bioinformatics methods - Nature

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Oct 1, 2013 (3 years and 6 months ago)

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Supplementary Material and Methods


CodeLink
TM

microarrays analysis of gene expression profiles.


CodeLink
TM

Human 20K Expression Bioarrrays (GE Healthcare, formerly Amersham
Biosciences, Piscataway, NJ)

containing approximately 20.000 gene probes derived
from well
-
annotated mRNA sequences, were used to analyze gene expression profiles.
Except where indicated, all reagents for labeling and hybridization were provided in the
CodeLink
TM

expression assay reagent kit. RNA was isolated with TRIreagent (Sigma,
St
. Louis, MO) and its integrity was assessed using an Agilent 2100 Bioanalyser
(Agilent, Palo Alto, CA). Double stranded cDNA and biotin
-
labeled cRNA were
generated following manufacturer’s instructions, except that biotin
-
16
-
UTP (Roche
Applied Science, Pen
zberg, Germany) was used instead of biotin
-
11
-
UTP. Biotin
-
labeled cRNA was purified on an RNeasy column (Qiagen, Valencia, California),
quantified by UV spectrophotometry, and analyzed

for integrity using an Agilent 2100
Bioanalyser. Then, 10 μg of cRNA were fragmented by heating at 94ºC for 20 minutes
in fragmentation buffer, and subsequently diluted in hybridization buffer and hybridized
to CodeLink
TM

Bioarrrays for 20 hours at 37ºC i
n an Innova 40 shaking incubator (New
Brunswick, Edison, NJ) at 300 rpm. After hybridization, microarrays were washed in
0.75x TNT buffer (1x TNT: 0.15 M NaCl, 0.05% Tween
-
200, 1 M Tris
-
HCl pH=7.6,)
for 1 hour at 46ºC, incubated with Cy5
-
streptavidin for 3
0 minutes at room temperature,
washed in 1x TNT four times for 5 minutes each followed by two rinses in 0.1x SSC,
0.05% Tween
-
20, and then dried by centrifugation. Slides were scanned in an Axon
GenePix Scanner (Arlington, TX) and analyzed using CodeLink
TM

Expression Analysis
Software (GE Healthcare).


Background extraction and data normalization.


After scanning, background correction for
CodeLink
TM

Human 20K Expression
Bioarrrays
expression was carried out using

the

normexp

method available in

the

Biocond
uctor
codelink

package developed by Díez
et al
.
In this step, those genes
showing L (low, Signal Noise Ratio

(SNR)
<

1) and G (good, SNR


1) flags are
selected for later normalization and analysis
. Concerning expression data normalization,
Cyclic Loess met
hod was implemented in R using the Bioconductor
affy

package and
the
normalize.loess

function and parameters as described by Wu
et al
.


Identification of g
ene
s differentially regulated and functional analysis
.


For differen
tial gene expression analysis

St
udent`s
T
-
Test and non
-
parametric Mann
-
Whitney U test were performed. Obtained p
-
values were adjusted by Benjamini
-
Hochberg method for False Discovery Rate (FDR) correction required in multiple
testing approaches. Thos
e genes exhibiting q
-
value <0.01

were
selected as differentially

expressed genes among classes.

The set of differentially expressed genes

between classes

was analyzed with the
Expression Analysis Systematic Explorer

function
(EASE,
http://david.abcc.ncifcrf.gov/ease/ease.jsp
)

implemented in Me
V software development
by TIGR

(http://www.tm4.org)

in order to

identify overrepresented GO terms

(Cellular
Component, Molecular Function, Biological Process)
. Fisher‘s exact test with
Bonferroni correction for multiple testing was

used for comparisons.

Ge
ne Set Enrichment Analyses (GSEA, see Subramanian
et al
.) were carried out using
publicly available Biocarta pathways (
www.biocarta.com
)
. In all cases, wei
ghted
enrichment statistic and Student’s T
-
Test metric for r
anked gene lists were
employed;

also,

statistical significance was determined using permutation testing (1000
permutations).

Gene sets including less than 15 members were excluded from the
enrichment analysis. Following non
-
parametric Kolmogorov
-
Smirnoff t
est, those
set of
genes

with FDR<0.25 were considered significantly enriched among classes (stable vs
unstable subgroups)
.



REFERENCES


Díez D, Álvarez R, Dopazo A.

C
odelink: An R package for analysis of GE Healthcare Gene Expression Bioarrays.

Bioinforma
tics. 2007 Mar 7.


Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy
SL, Golub TR, Lander ES, Mesirov JP.

Gene set enrichment analysis: a knowledge
-
based approach for interpreting genome
-
wide expression
profiles.

Proc Natl Acad Sci U S A. 2005 Oct 25;102(43):15545
-
50.


Wu W, Dave N, Tseng GC, Richards T, Xing EP, Kaminski N.

Comparison of normalization methods for CodeLink Bioarray data.

BMC Bioinformatics
. 2005 Dec 28;6:309.