robtest {DiPhiSeq} | R Documentation |
Calls the robnb function to estimate the coefficients, and then construct the statistical tests for DD and DE. It works for a single gene. y1 and y2 are count vectors for a single gene. diphiseq calls this function to do the calculation for each gene. Normal users often don't need to use this function directly.
robtest(y1, log.depth1, y2, log.depth2, c.tukey.beta = 4, c.tukey.phi = 4)
y1 |
counts from group 1. a vector. |
log.depth1 |
log(sequencing depths) for samples in group 1. a vector. |
y2 |
counts from group 2. a vector. |
log.depth2 |
log(sequencing depths) for samples in group 2. a vector. |
c.tukey.beta |
The c value for beta in Huber function. The default value, 4, is typically regarded as appropriate and should work for most datasets. |
c.tukey.phi |
The c value for phi in Huber function. The default value, 4, is typically regarded as appropriate and should work for most datasets. |
A vector that contains the elements:
phi1
: the estimated dispersion of sample group 1.
phi2
: the estimated dispersion of sample group 2.
beta1
: the estimated (log) expression of sample group 1.
beta2
: the estimated (log) expression of sample group 2.
statistic.phi
: the z statistic for DD.
statistic.beta
: the z statistic for DE.
p.value.phi
: the p value for DD.
p.value.beta
: the p value for DE.
d1 <- runif(10, min=1, max=2)
d2 <- runif(15, min=1, max=2)
y1 <- rnbinom(10, size=1, mu=d1*50)
y2 <- rnbinom(15, size=1, mu=d2*50)
res <- robtest(y1, log(d1), y2, log(d2))