R: Haplotype-Aware Hidden Markov Model for RNA

# Haplotype-Aware Hidden Markov Model for RNA

## Documentation for package ‘hahmmr’ version 1.0.0

- DESCRIPTION file
- Package README

## Help Pages

acen_hg19 | centromere regions (hg19)
acen_hg38 | centromere regions (hg38)
analyze_allele | Analyze allele profile
analyze_joint | Analyze allele and expression profile
bulk_example | example pseudobulk dataframe
chrom_sizes_hg19 | chromosome sizes (hg19)
chrom_sizes_hg38 | chromosome sizes (hg38)
dbbinom | Beta-binomial distribution density function A distribution is beta-binomial if p, the probability of success, in a binomial distribution has a beta distribution with shape parameters alpha > 0 and beta > 0 For more details, see extraDistr::dbbinom
df_allele_example | example allele count dataframe
dpoilog | Returns the density for the Poisson lognormal distribution with parameters mu and sig
fit_lnpois_cpp | Fit MLE of log-normal Poisson model
forward_back_allele | Forward-backward algorithm for allele HMM
gaps_hg19 | genome gap regions (hg19)
gaps_hg38 | genome gap regions (hg38)
gene_counts_example | example gene expression counts matrix
get_allele_bulk | Aggregate into pseudobulk alelle profile
get_bulk | Produce combined bulk expression and allele profile
gtf_hg19 | gene model (hg19)
gtf_hg38 | gene model (hg38)
gtf_mm10 | gene model (mm10)
likelihood_allele | Only compute total log likelihood from an allele HMM
logSumExp | logSumExp function
l_bbinom | calculate joint likelihood of allele data
l_lnpois | calculate joint likelihood of a PLN model
plot_bulks | Plot a group of pseudobulk HMM profiles
plot_psbulk | Plot a pseudobulk HMM profile
pre_likelihood_hmm | HMM object for unit tests
ref_hca | reference expression magnitudes from HCA
ref_hca_counts | reference expression counts from HCA
run_allele_hmm_s5 | Run a 5-state allele-only HMM - two theta levels
run_joint_hmm_s15 | Run 15-state joint HMM on a pseudobulk profile
segs_example | example CNV segments dataframe
vcf_meta | example VCF header