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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/>.
Version: | 1.0.0 |
Depends: | R (≥ 4.1.0) |
Imports: | data.table, dplyr, GenomicRanges, ggplot2, glue, IRanges, methods, patchwork, Rcpp, stringr, tibble, zoo |
LinkingTo: | Rcpp, RcppArmadillo, roptim |
Suggests: | ggrastr, testthat |
Published: | 2023-10-25 |
DOI: | 10.32614/CRAN.package.hahmmr |
Author: | Teng Gao [aut, cre], Evan Biederstedt [aut], Peter Kharchenko [aut] |
Maintainer: | Teng Gao <tgaoteng at gmail.com> |
License: | MIT + file LICENSE |
NeedsCompilation: | yes |
Materials: | README |
CRAN checks: | hahmmr results |
Reference manual: | hahmmr.pdf |
Package source: | hahmmr_1.0.0.tar.gz |
Windows binaries: | r-devel: hahmmr_1.0.0.zip, r-release: hahmmr_1.0.0.zip, r-oldrel: hahmmr_1.0.0.zip |
macOS binaries: | r-release (arm64): hahmmr_1.0.0.tgz, r-oldrel (arm64): hahmmr_1.0.0.tgz, r-release (x86_64): hahmmr_1.0.0.tgz, r-oldrel (x86_64): hahmmr_1.0.0.tgz |
Reverse imports: | numbat |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.