Package: hahmmr 1.0.0

hahmmr: Haplotype-Aware Hidden Markov Model for RNA

Haplotype-aware Hidden Markov Model for RNA (HaHMMR) is a method for detecting copy number variations (CNVs) from bulk RNA-seq data. Additional examples, documentations, and details on the method are available at <https://github.com/kharchenkolab/hahmmr/>.

Authors:Teng Gao [aut, cre], Evan Biederstedt [aut], Peter Kharchenko [aut]

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hahmmr.pdf |hahmmr.html✨
hahmmr/json (API)

# Install 'hahmmr' in R:
install.packages('hahmmr', repos = c('https://teng-gao.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.18 score 1 packages 4 scripts 301 downloads 16 exports 55 dependencies

Last updated 1 years agofrom:466187fcff. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 25 2024
R-4.5-win-x86_64OKOct 25 2024
R-4.5-linux-x86_64OKOct 25 2024
R-4.4-win-x86_64OKOct 25 2024
R-4.4-mac-x86_64OKOct 25 2024
R-4.4-mac-aarch64OKOct 25 2024
R-4.3-win-x86_64OKOct 25 2024
R-4.3-mac-x86_64OKOct 25 2024
R-4.3-mac-aarch64OKOct 25 2024

Exports:analyze_alleleanalyze_jointdbbinomdpoilogfit_lnpois_cppforward_back_alleleget_allele_bulkget_bulkl_bbinoml_lnpoislikelihood_allelelogSumExpplot_bulksplot_psbulkrun_allele_hmm_s5run_joint_hmm_s15

Dependencies:askpassBiocGenericsclicolorspacecurldata.tabledplyrfansifarvergenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegtablehttrIRangesisobandjsonlitelabelinglatticelifecyclemagrittrMASSMatrixmgcvmimemunsellnlmeopensslpatchworkpillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangroptimS4VectorsscalesstringistringrsystibbletidyselectUCSC.utilsutf8vctrsviridisLitewithrXVectorzlibbioczoo

Readme and manuals

Help Manual

Help pageTopics
centromere regions (hg19)acen_hg19
centromere regions (hg38)acen_hg38
Analyze allele profileanalyze_allele
Analyze allele and expression profileanalyze_joint
example pseudobulk dataframebulk_example
chromosome sizes (hg19)chrom_sizes_hg19
chromosome sizes (hg38)chrom_sizes_hg38
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::dbbinomdbbinom
example allele count dataframedf_allele_example
Returns the density for the Poisson lognormal distribution with parameters mu and sigdpoilog
Fit MLE of log-normal Poisson modelfit_lnpois_cpp
Forward-backward algorithm for allele HMMforward_back_allele
genome gap regions (hg19)gaps_hg19
genome gap regions (hg38)gaps_hg38
example gene expression counts matrixgene_counts_example
Aggregate into pseudobulk alelle profileget_allele_bulk
Produce combined bulk expression and allele profileget_bulk
gene model (hg19)gtf_hg19
gene model (hg38)gtf_hg38
gene model (mm10)gtf_mm10
calculate joint likelihood of allele datal_bbinom
calculate joint likelihood of a PLN modell_lnpois
Only compute total log likelihood from an allele HMMlikelihood_allele
logSumExp functionlogSumExp
Plot a group of pseudobulk HMM profilesplot_bulks
Plot a pseudobulk HMM profileplot_psbulk
HMM object for unit testspre_likelihood_hmm
reference expression magnitudes from HCAref_hca
reference expression counts from HCAref_hca_counts
Run a 5-state allele-only HMM - two theta levelsrun_allele_hmm_s5
Run 15-state joint HMM on a pseudobulk profilerun_joint_hmm_s15
example CNV segments dataframesegs_example
example VCF headervcf_meta