peelingTwo | R Documentation |
This function applies a modified version of the peeling algorithm originally described in Walter et al.,
peelingTwo(X, Y, posDT, k, threshold = NULL)
X |
A matrix of normalized gene-level copy number data (rows = genes, columns = subjects). |
Y |
A matrix of normalized gene-level copy number data (rows = genes, columns = subjects). |
posDT |
A data frame containing genomic position information for the genes in X. |
k |
The location (row of X and Y) containing the peak that will be peeled. |
threshold |
A tuning parameter that controls the size of the peeled region. Rows in which rowMeans(X) - rowMeans(Y) are less than threshold will not be peeled. |
(PMID 21183584) to remove a peak from the copy number differences and define a genomic interval of interest
around the peak.
When tumor genomes from two cohorts are compared, there may be multiple regions that harbor
copy number differences. For example, gains or losses may be present in only one of the two cohorts,
and this could give rise to copy number differences. Alternatively, the same region of the genome
may exhibit gain or loss in both cohorts. If the magnitudes of the common gain or loss are distinct,
then this also gives rise to copy number differences. The locus that harbors the most extreme difference,
k, provides a point estimate for the underlying driver gene that gives rise to the difference. Loci
near k may also be affected by the underlying difference in copy number. The peeling procedure for
two cohorts is applied to "nullify" entries of both X and Y that contribute to the alteration at k,
thus making it possible to identify other regions of the genome that harbor copy number differences.
This function is called by peelingTwoIterate
.
A list containing three elements: X, Y, and interval. X and Y are updated versions of the input copy number matrices X and Y in which the peak at k has been removed, and interval is genomic region containing k. By construction, interval cannot extend beyond the chromosome arm containing k.
luad=pD[["X"]] lusc=pD[["Y"]] posDT=pD[["posDT"]] kDiff=which.max(rowMeans(luad)-rowMeans(lusc)) peeledDiff=peelingTwo(X=luad,Y=lusc,posDT=posDT,k=kDiff,threshold=NULL)
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