compute_ambient_pvalues: Compute p-values for observed multinomial log-likelihoods
In zh542370159/dropSplit: Automatically identify cell-containing and empty droplets for droplet-based scRNAseq data using dropSplit
compute_ambient_pvalues R Documentation
Compute p-values for observed multinomial log-likelihoods
Description
Compute p-values for observed multinomial log-likelihoods
Usage
compute_ambient_pvalues(umis_per_bc, obs_loglk, sim_n, sim_loglk)
Arguments
umis_per_bc
UMI counts per barcode
obs_loglk
Observed log-likelihoods of each barcode deriving from an ambient profile
sim_n
Multinomial N for simulated log-likelihoods
sim_loglk
Simulated log-likelihoods of maxtix. nrow=length(sim_n), ncol=num_simulations
Value
pvalues
zh542370159/dropSplit documentation built on June 19, 2022, 2:49 p.m.
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| compute_ambient_pvalues | R Documentation |
Compute p-values for observed multinomial log-likelihoods
Description
Compute p-values for observed multinomial log-likelihoods
Usage
compute_ambient_pvalues(umis_per_bc, obs_loglk, sim_n, sim_loglk)
Arguments
umis_per_bc |
UMI counts per barcode |
obs_loglk |
Observed log-likelihoods of each barcode deriving from an ambient profile |
sim_n |
Multinomial N for simulated log-likelihoods |
sim_loglk |
Simulated log-likelihoods of maxtix. nrow=length(sim_n), ncol=num_simulations |
Value
pvalues
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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