evalLogLikZINB {LineagePulse} | R Documentation |
This liklihood function is appropriate for sequencing data with high drop out rate, commonly observed in single cell data (e.g. scRNA-seq). This is the core function used for every likelihood evaluation in LineagePulse, such as maximum likelihood-based estimation. It operates on a vector of counts, such as observations of a gene. Note that for the sake of numerical stability, lower bounds on loglikelihood terms are implemented.
evalLogLikZINB(vecCounts, vecMu, vecDisp, vecPi, vecidxNotZero, vecidxZero)
vecCounts |
(count vector number of samples) Observed read counts, not observed are NA. |
vecMu |
(vector number of samples) Negative binomial mean parameter. |
vecDisp |
(scalar vector number of samples) Negative binomial dispersion parameters. |
vecPi |
(probability vector number of samples) Drop-out rate estimates. |
vecidxNotZero |
(bool vector number of samples) Whether observation is larger than zero. |
vecidxZero |
(bool vector number of samples) Whether observation is zero. |
scaLogLik (scalar) Likelihood under zero-inflated negative binomial model.
David Sebastian Fischer