get_bbgpMeanStd: Computing means and standard deviations for the BBGP (beta...
In GPrank: Gaussian Process Ranking of Multiple Time Series

Description Usage Arguments Value Author(s) Examples

Function for obtaining the posterior means and standard deviations for the frequencies (counts divided by sequencing depth) by using the counts and sequencing depth values in a beta binomial model. Parameters (alpha and beta) of the model are set to 1 by default, which keeps symmetry between f and (1-f), where f denotes the frequency valued between (0,1).

1	get_bbgpMeanStd(x, counts, seq_depth, alpha = 1, beta = 1)

`x`	Time vector
`counts`	Vector containing the counts data at the given time points.
`seq_depth`	Vector containing the sequencing depth values at the given time points.
`alpha`	alpha parameter of the beta binomial model.
`beta`	beta parameter of the beta binomial model.

Return list containing the posterior means and standard deviations of the frequencies at the time points where sequencing depth is larger than zero. x vector is updated so that it excludes the time points with zero sequencing depth, i.e. time points at which no data have been observed. Posterior means and standard deviations and the updated x vecor are assigned to the list elements named 'posteriorMean', 'posteriorStd', and 'time', respectively.

Hande Topa, hande.topa@helsinki.fi

x=c(1,2,3,4,5)
counts=c(12,54,32,0,34)
seq_depth=c(50,70,35,0,40)
bbgp=get_bbgpMeanStd(x,counts,seq_depth)
x=bbgp$time # updated time vector
y=bbgp$posteriorMean # posterior means
v=bbgp$posteriorStd^2 # posterior variances