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Fig. 6.4
Execution of the example script and display of results
a number of easy-to-use wrapper functions for often recurring analysis steps
when dealing with Affymetrix array, in particular regarding preprocessing and
expression value filtering. The
limma
package [290] provides functionality for
the analysis of gene expression data using linear models. The last three pack-
ages that are loaded are required for the annotation step, that is, the search
for relevant PubMed articles: the
hgu95av2.db
annotation data package [63]
contains annotation data for the Affymetrix chip hgu95av2 (Human Genome
U95), the
annotate
package [103] provides functions to associate meta-data
of different kind and from different sources with the analyzed experimental
data, and
XML
[181] is simply required for proper HTML formatting.
When the required R and Bioconductor packages have been loaded, lines
11-14 load the input data. The CEL files are located in the
spikein/
di-
rectory and
spikein pdata.txt
is the text file containing the corresponding
pheno data (i.e. meta-data on the CEL data sets). The pheno data are read
using the standard R function for reading table data, while the function
ReadAffy
from the
affy
package is used to create an
AffyBatch
object from
the pheno data and the CEL data. Next (line 17), the
pre.process
func-
tion of the
AffyExpress
package is called for preprocessing the data in the
AffyBatch
object and creating the corresponding
ExprSet
.Usingthe
Filter
function of the
AffyExpress
package, line 20 filters the contained data sets
so that only those remain in the
ExprSet
that have at least 3 chips with a
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