ratexample | R Documentation |
Log ratio data for 5 breast cancer genomes, derived using Representational Oligonucleotide Microarray Analysis (ROMA), an array-based hybridization method that uses genomic complexity reduction based on representations.
data(ratexample)
a log ratio matrix
with 83055 rows, one per
oligonucleotide probe, and 5 columns, one for each breast tumor sample.
The values are natural log copy number ratios, consistent with
data in segexample
(segmented data for these tumors) and
normsegs
. These copy number ratios are normalized using an
intensity-based lowess curve fitting algorithm.
a log ratio matrix
with 83055 rows, one per
oligonucleotide probe, and 5 columns, one for each breast tumor sample.
Hicks, J. et al. Novel patterns of genome rearrangement and their association with survival in breast cancer. Genome Res. 2006. 16:1465–1479. doi: 10.1101/gr.5460106
CNpreprocessing
for pre-process DNA copy number (CN)
data for detection of CN events.
makeCNPmask
for creating a mask given a set of
copy number events.
applyCNPmask
for applying a mask to a set of
copy number events.
## Loading log ratio dataset data(ratexample) ## Plot the whole genome log ratio data for the first profile "WZ1" ## Note X and Y chromosomes at the far right of the plot plot(ratexample[,"WZ1"], ylab="log ratio", xlab="position")
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