Description Usage Arguments Details Value Author(s) References Examples
This function uses the GCadjustCopy
function to convert
a matrix of count data into absolute copy number estimates, then calculates the log2
fold change ratio and segments these values.
1 2 3 4 5 6 | ## S4 method for signature 'data.frame,matrix'
relativeCN(input.windows, input.counts, gc.params = NULL,
..., verbose = TRUE)
## S4 method for signature 'GRanges,matrix'
relativeCN(input.windows, input.counts, gc.params = NULL,
..., verbose = TRUE)
|
input.windows |
A |
input.counts |
A matrix of counts. The first column must be for the control state, and the second column must be for the treatment state. |
gc.params |
A |
... |
Further parameters passed to |
verbose |
Whether to print the progess of processing. |
The algorithm used to call the copy number regions is Circular Binary
Segmentation (Olshen et al. 2004). Weights for each window, that are the inverse of
the variance, calculated with the delta method, are always used. Windows or regions
that were not in the segmentation result are given the value NA
.
If gc.params
is NULL
, then no correction for mappability
or GC content is done. This can be done when the bias in both treatment and control
samples is assumed to be equal. If gc.params
is specified, then absolute
copy numbers are estimated with GCadjustCopy
for each condition,
which corrects for mappability and then GC content, before estimating absolute
copy numbers. The ratio of estimated absolute copy numbers is segmented, to
calculate relative copy numbers.
If gc.params
was given, then a AdjustedCopyEstimate
object.
Otherwise, a CopyEstimate
object. The copy number ratios are
on the linear scale, not log2.
Dario Strbenac
Olshen, A. B., Venkatraman, E. S., Lucito, R., and Wigler, M. (2004). Circular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics 5: 557-572
1 2 3 4 5 6 | inputs <- data.frame(chr = c("chr1", "chr1", "chr1", "chr2", "chr2"),
start = c(1, 50001, 100001, 1, 10001),
end = c(50000, 100000, 150000, 10000, 20000))
counts <- matrix(c(25, 39, 3, 10, 22, 29, 38, 5, 19, 31), nrow = 5)
colnames(counts) <- c("Control", "Treatment")
relativeCN(inputs, input.counts = counts, p.method = "perm")
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.