Description Usage Arguments Details Value Examples
Collect information and perform statistics of depth of coverage in relation with GC-content.
1 2 3 4 5 6 | gc.sample.stats(file, col_types = "c--dd----d----", buffer = 33554432,
parallel = 2L, verbose = TRUE)
gc.summary.plot(gc_list, mean.col = 1, median.col = 2,
scale.subset = 1.5, ...)
mean_gc(gc_list)
median_gc(gc_list)
|
file |
name of a file in the seqz format. |
col_types |
a string describing the classes of each columns of the
input file (see |
buffer |
maximal size of each chunk in bytes(see
|
parallel |
integer, number of threads used to process a seqz file
(see |
verbose |
logical. If TRUE (the default) the function retuns information in the console. |
gc_list |
a normal or tumor list resulting from the
|
mean.col |
color for the mean in the summary plot. |
median.col |
color for the median in the summary plot. |
scale.subset |
scale the depth values to sho in the plot. A value of 1 will show the average depth at the center of the plot. |
... |
additional parametrers from |
gc.sample.stats
extracts depths and GC-content inforation for the
tumor and the control samples from an seqz file
it returns a list with 3 elements: file.metrics
, normal
and
tumor
.
file.metrics
is a data.frame
serving as index of the seqz
file; the normal
and tumor
objects contains each 3 ojects:
gc
, depth
and n
.
gc
and depth
are vectors containing the recorded values of,
respectively, GC and coverage depth. the n
object is a matrix
gc
xdepth
, recording the number of time a certain
gc
/depth
pairs is observed in the data.
A list with the following elements:
file.metrics |
index of the seqz file. |
tumor |
GC and coverage depth observations in the tumor sample. |
normal |
GC and coverage depth observations in the control sample. |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ## Not run:
data.file <- system.file("extdata", "example.seqz.txt.gz", package = "sequenza")
# read all the chromosomes:
gc_info <- gc.sample.stats(data.file)
# mean values of depth coverage vs GC content
mean_gc(gc_info$normal)
# plot the information for the tumor and normal samples
par(mfrow=c(1, 2))
gc.summary.plot(gc_info$normal, main = "Normal GC stats")
gc.summary.plot(gc_info$tumor, main = "Tumor GC stats")
## End(Not run)
|
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