Must have packages on the Rstudio while doing NGS (ChIP/RNA/DNAme) related analysis

Question

[Dataminer]

Hi,

I was wondering what all packages of R people have on their Rstudio. Specifically the people involved in NGS data analysis.

I know, of the compatibility issues of some packages with the R version installed for Rstudio. How do you all circumvent this issue?

Overall it will be good to have a list of must have R packages that can be installed on a Rstudio running certain version of R.

Out of curiosity, I really want to know what is going around in this area and how people are dealing with it. For me whenever certain things do not work on my R studio due to compatibility issue I just run it outside Rstudio on a different version. But, I am sure others must be having different take on this issue.

Kindly share your valuable thoughts.

Answer 1

[Devon Ryan]

Most people here have at least the following:

acepack        dichromat       gtools        mime           R.utils
annotate       digest          highr         munsell        S4Vectors
AnnotationDbi  evaluate        Hmisc         nlme           scales
Biobase        foreign         htmltools     nnet           snow
BiocGenerics   formatR         IRanges       plyr           spatial
BiocInstaller  Formula         KernSmooth    png            stringi
BiocParallel   futile.logger   knitr         proto          stringr
Biostrings     futile.options  labeling      RColorBrewer   survival
bitops         gdata           lambda.r      Rcpp           XML
boot           genefilter      lattice       RcppArmadillo  xtable
caTools        geneplotter     latticeExtra  reshape2       XVector
class          GenomeInfoDb    locfit        rmarkdown      yaml
cluster        GenomicRanges   magrittr      R.methodsS3    zlibbioc
codetools      ggplot2         markdown      R.oo
colorspace     gplots          MASS          rpart
DBI            gridExtra       Matrix        Rsamtools
DESeq2         gtable          mgcv          RSQLite

We have a couple directories of packages (for different architectures and versions) that people can just link to or copy over.

Edit: I should note that I don't really use R-studio server much myself, though I run the server. I roll old-school and just use plain R.