Henrik Bengtsson [aut, cre, cph],
  Constantin Ahlmann-Eltze [ctb],
  Hector Corrada Bravo [ctb],
  Robert Gentleman [ctb],
  Jan Gleixner [ctb],
  Peter Hickey [ctb],
  Ola Hossjer [ctb],
  Harris Jaffee [ctb],
  Dongcan Jiang [ctb],
  Peter Langfelder [ctb],
  Brian Montgomery [ctb],
  Angelina Panagopoulou [ctb],
  Hugh Parsonage [ctb],
  Jakob Peder Pettersen [ctb]

High-performing functions operating on rows and columns of matrices, e.g. col / rowMedians(), col / rowRanks(), and col / rowSds().  Functions optimized per data type and for subsetted calculations such that both memory usage and processing time is minimized.  There are also optimized vector-based methods, e.g. binMeans(), madDiff() and weightedMedian().

S4 generic functions used in Bioconductor

The package defines many S4 generic functions used in Bioconductor.

R (>= 4.0.0), methods, utils, graphics, stats

Biobase, S4Vectors, IRanges, GenomicRanges, DelayedArray,
Biostrings, Rsamtools, AnnotationDbi, affy, affyPLM, DESeq2,
flowClust, MSnbase, annotate, RUnit

S3-classes-as-S4-classes.R utils.R normarg-utils.R
replaceSlots.R aperm.R append.R as.data.frame.R as.list.R
as.vector.R cbind.R do.call.R duplicated.R eval.R Extremes.R
format.R funprog.R get.R grep.R is.unsorted.R lapply.R mapply.R
match.R mean.R nrow.R order.R paste.R rank.R rep.R
row_colnames.R sets.R sort.R start.R subset.R t.R table.R
tapply.R unique.R unlist.R unsplit.R relist.R var.R which.R
which.min.R boxplot.R image.R density.R IQR.R mad.R residuals.R
weights.R xtabs.R annotation.R combine.R dbconn.R dge.R dims.R
fileName.R normalize.R Ontology.R organism_species.R path.R
plotMA.R plotPCA.R score.R strand.R toTable.R type.R
updateObject.R testPackage.R zzz.R

Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns, friendly and fast character-separated-value read/write. Offers a natural and flexible syntax, for faster development.

CBW Workshop 2024: Pharmacogenomics Data Analysis