Type: Package
Package: clustermole
Title: Unbiased Cell Type Identification of Single-Cell Transcriptomic
        Data
Version: 1.0.0
Authors@R: 
    person(given = "Igor",
           family = "Dolgalev",
           role = c("aut", "cre"),
           email = "igor.dolgalev@nyumc.org")
Description: A typical computational pipeline to process single-cell RNA sequencing (scRNA-seq) data  involves clustering of cells. Assignment of cell type labels to those clusters is often a time-consuming process that involves manual inspection of the cluster marker genes complemented with a detailed literature search. This is especially challenging if you are not familiar with all the captured subpopulations or have unexpected contaminants. 'clustermole' provides a comprehensive meta collection of cell identity markers for thousands of human and mouse cell types sourced from a variety of databases as well as methods to query them.
License: MIT + file LICENSE
URL: https://github.com/igordot/clustermole
BugReports: https://github.com/igordot/clustermole/issues
Depends: R (>= 3.4)
Imports: dplyr, GSVA (>= 1.26.0), magrittr, methods, rlang (>= 0.1.2),
        tibble, tidyr, utils
Suggests: covr, roxygen2, testthat (>= 2.1.0), knitr, rmarkdown
biocViews:
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-15 00:50:36 UTC; id460
Author: Igor Dolgalev [aut, cre]
Maintainer: Igor Dolgalev <igor.dolgalev@nyumc.org>
Repository: CRAN
Date/Publication: 2020-01-20 10:00:02 UTC
Built: R 3.5.3; ; 2020-01-26 07:30:42 UTC; windows
