--- /tmp/r-bioc-scater-1.18.3+ds-4241exo49/debian/r-bioc-scater_1.18.3+ds-4_all.deb +++ r-bioc-scater_1.18.3+ds-4_all.deb ├── file list │ @@ -1,3 +1,3 @@ │ -rw-r--r-- 0 0 0 4 2021-02-07 10:34:46.000000 debian-binary │ --rw-r--r-- 0 0 0 2080 2021-02-07 10:34:46.000000 control.tar.xz │ +-rw-r--r-- 0 0 0 2088 2021-02-07 10:34:46.000000 control.tar.xz │ -rw-r--r-- 0 0 0 529068 2021-02-07 10:34:46.000000 data.tar.xz ├── control.tar.xz │ ├── control.tar │ │ ├── file list │ │ │ @@ -1,3 +1,3 @@ │ │ │ drwxr-xr-x 0 root (0) root (0) 0 2021-02-07 10:34:46.000000 ./ │ │ │ --rw-r--r-- 0 root (0) root (0) 1099 2021-02-07 10:34:46.000000 ./control │ │ │ +-rw-r--r-- 0 root (0) root (0) 1116 2021-02-07 10:34:46.000000 ./control │ │ │ -rw-r--r-- 0 root (0) root (0) 3593 2021-02-07 10:34:46.000000 ./md5sums │ │ ├── ./control │ │ │ @@ -1,15 +1,15 @@ │ │ │ Package: r-bioc-scater │ │ │ Version: 1.18.3+ds-4 │ │ │ Architecture: all │ │ │ Maintainer: Debian R Packages Maintainers │ │ │ Installed-Size: 660 │ │ │ Depends: r-base-core (>= 4.0.3-1), r-api-4.0, r-api-bioc-3.12, r-bioc-singlecellexperiment, r-cran-ggplot2, r-cran-gridextra, r-cran-matrix, r-bioc-biocgenerics, r-bioc-s4vectors, r-bioc-summarizedexperiment, r-bioc-delayedarray, r-bioc-delayedmatrixstats, r-bioc-biocneighbors, r-bioc-biocsingular, r-bioc-biocparallel, r-bioc-scuttle, r-cran-rlang, r-cran-ggbeeswarm, r-cran-viridis │ │ │ Recommends: r-cran-testthat, r-bioc-destiny, r-cran-uwot, r-cran-nmf, r-cran-rtsne, r-bioc-dropletutils, r-cran-pheatmap │ │ │ -Suggests: r-bioc-biocstyle, r-bioc-biomart, r-cran-cowplot, r-cran-knitr, r-cran-robustbase, r-cran-rmarkdown, r-bioc-biobase │ │ │ +Suggests: r-bioc-biocstyle, r-bioc-biomart, r-cran-cowplot, r-cran-knitr, r-bioc-scrnaseq, r-cran-robustbase, r-cran-rmarkdown, r-bioc-biobase │ │ │ Section: gnu-r │ │ │ Priority: optional │ │ │ Homepage: https://bioconductor.org/packages/scater/ │ │ │ Description: Single-Cell Analysis Toolkit for Gene Expression Data in R │ │ │ A collection of tools for doing various analyses of │ │ │ single-cell RNA-seq gene expression data, with a focus on │ │ │ quality control and visualization.