Description Usage Arguments Details Value Author(s) References See Also Examples
Filters all vectors in list based on specified chromosome(s) of interest, minimum and maximum read depths, missing data, mappability score threshold
1 2 3 |
data |
data.table object that contains an arbitrary number of components. Should include ‘chr’, ‘tumDepth’. All vector elements must have the same number of rows where each row corresponds to information pertaining to a chromosomal position. |
chrs |
|
minDepth |
|
maxDepth |
|
positionList |
|
map |
|
mapThres |
|
centromeres |
data.frame containing list of centromere regions. This should contain 3 columns: chr, start, and end. If this argument is used, then data at and flanking the centromeres will be removed. |
centromere.flankLength |
Integer indicating the length (in base pairs) to the left and to the right of the centromere designated for removal of data. |
All vectors in the input data.table object, and map
, must all have the same number of rows.
The same data.table
object containing filtered components.
Gavin Ha <gavinha@gmail.com>
Ha, G., Roth, A., Khattra, J., Ho, J., Yap, D., Prentice, L. M., Melnyk, N., McPherson, A., Bashashati, A., Laks, E., Biele, J., Ding, J., Le, A., Rosner, J., Shumansky, K., Marra, M. A., Huntsman, D. G., McAlpine, J. N., Aparicio, S. A. J. R., and Shah, S. P. (2014). TITAN: Inference of copy number architectures in clonal cell populations from tumour whole genome sequence data. Genome Research, 24: 1881-1893. (PMID: 25060187)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | infile <- system.file("extdata", "test_alleleCounts_chr2.txt",
package = "TitanCNA")
tumWig <- system.file("extdata", "test_tum_chr2.wig", package = "TitanCNA")
normWig <- system.file("extdata", "test_norm_chr2.wig", package = "TitanCNA")
gc <- system.file("extdata", "gc_chr2.wig", package = "TitanCNA")
map <- system.file("extdata", "map_chr2.wig", package = "TitanCNA")
#### LOAD DATA ####
data <- loadAlleleCounts(infile, genomeStyle = "NCBI")
#### GC AND MAPPABILITY CORRECTION ####
cnData <- correctReadDepth(tumWig, normWig, gc, map)
#### READ COPY NUMBER FROM HMMCOPY FILE ####
logR <- getPositionOverlap(data$chr, data$posn, cnData)
data$logR <- log(2^logR) #use natural logs
#### FILTER DATA FOR DEPTH, MAPPABILITY, NA, etc ####
filtereData <- filterData(data, as.character(1:24), minDepth = 10,
maxDepth = 200, map = NULL, mapThres=0.9)
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