deepSNV | R Documentation |
This generic function can handle different types of inputs for the test and control experiments. It either reads from two .bam files,
uses two matrices of nucleotide counts, or re-evaluates the test results from a deepSNV-class
object. The actual test is a
likelihood ratio test of a (beta-)binomial model for the individual nucleotide counts on each position under the hypothesis that both experiments share the same parameter,
and the alternative that the parameters differ. Because the difference in degrees of freedom is 1, the test statistic D = -2 \log \max{L_0}/\max{L_1}
is asymptotically distributed as χ_1^2. The statistic may be tuned by a nucleotide specific Dirichlet prior that is learned across all genomic sites,
see estimateDirichlet
. If the model is beta-binomial, a global dispersion parameter is used for all sites. It can be learned with estimateDispersion
.
deepSNV(test, control, ...) ## S4 method for signature 'matrix,matrix' deepSNV(test,control, alternative = c('greater', 'less', 'two.sided'), dirichlet.prior = NULL, pseudo.count=1, combine.method = c("fisher", "max", "average"), over.dispersion = 100, model = c("bin", "betabin"), ...) ## S4 method for signature 'deepSNV,missing' deepSNV(test, control, ...) ## S4 method for signature 'character,character' deepSNV(test, control, regions, q=25, s=2, head.clip=0, ...) ## S4 method for signature 'matrix,character' deepSNV(test, control, regions, q=25, s=2, ...) ## S4 method for signature 'character,matrix' deepSNV(test, control, regions, q=25, s=2, ...)
test |
The test experiment. Either a .bam file, or a matrix with nucleotide counts, or a |
control |
The control experiment. Must be of the same type as test, or missing if test is a |
... |
Additional arguments. |
alternative |
The alternative to be tested. One of greater, less, or two.sided. |
dirichlet.prior |
A base-sepecific Dirichlet prior specified as a matrix. Default NULL. |
pseudo.count |
If dirichlet.prior=NULL, a pseudocount can be used to define a flat prior. |
combine.method |
The method to combine p-values. One of "fisher" (default), "max", or "average". See |
over.dispersion |
A numeric factor for the over.dispersion, if the model is beta-binomial. Default 100. |
model |
Which model to use. Either "bin", or "betabin". Default "bin". |
regions |
The regions to be parsed if test and control are .bam files. Either a |
q |
The quality arguement passed to |
s |
The strand argument passed to |
head.clip |
The head.clip argument passed to |
A deepSNV
object
Moritz Gerstung
## Short example with 2 SNVs at frequency ~10% regions <- data.frame(chr="B.FR.83.HXB2_LAI_IIIB_BRU_K034", start = 3120, stop=3140) ex <- deepSNV(test = system.file("extdata", "test.bam", package="deepSNV"), control = system.file("extdata", "control.bam", package="deepSNV"), regions=regions, q=10) show(ex) # show method plot(ex) # scatter plot summary(ex) # summary with significant SNVs ex[1:3,] # subsetting the first three genomic positions tail(test(ex, total=TRUE)) # retrieve the test counts on both strands tail(control(ex, total=TRUE)) ## Not run: Full example with ~ 100 SNVs. Requires an internet connection, but try yourself. # regions <- data.frame(chr="B.FR.83.HXB2_LAI_IIIB_BRU_K034", start = 2074, stop=3585) # HIVmix <- deepSNV(test = "http://www.bsse.ethz.ch/cbg/software/deepSNV/data/test.bam", control = "http://www.bsse.ethz.ch/cbg/software/deepSNV/data/control.bam", regions=regions, q=10) data(HIVmix) # attach data instead.. show(HIVmix) plot(HIVmix) head(summary(HIVmix))
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