bit64, curl, R.utils, knitr, xts, nanotime, zoo, yaml

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.

Matt Dowle [aut, cre],
  Arun Srinivasan [aut],
  Jan Gorecki [ctb],
  Michael Chirico [ctb],
  Pasha Stetsenko [ctb],
  Tom Short [ctb],
  Steve Lianoglou [ctb],
  Eduard Antonyan [ctb],
  Markus Bonsch [ctb],
  Hugh Parsonage [ctb],
  Scott Ritchie [ctb],
  Kun Ren [ctb],
  Xianying Tan [ctb],
  Rick Saporta [ctb],
  Otto Seiskari [ctb],
  Xianghui Dong [ctb],
  Michel Lang [ctb],
  Watal Iwasaki [ctb],
  Seth Wenchel [ctb],
  Karl Broman [ctb],
  Tobias Schmidt [ctb],
  David Arenburg [ctb],
  Ethan Smith [ctb],
  Francois Cocquemas [ctb],
  Matthieu Gomez [ctb],
  Philippe Chataignon [ctb],
  Declan Groves [ctb],
  Daniel Possenriede [ctb],
  Felipe Parages [ctb],
  Denes Toth [ctb],
  Mus Yaramaz-David [ctb],
  Ayappan Perumal [ctb],
  James Sams [ctb],
  Martin Morgan [ctb],
  Michael Quinn [ctb],
  @javrucebo [ctb],
  @marc-outins [ctb],
  Roy Storey [ctb],
  Manish Saraswat [ctb],
  Morgan Jacob [ctb],
  Michael Schubmehl [ctb],
  Davis Vaughan [ctb]

Analysis of Large-Scale Radio-Genomic Data

c(
  person("Venkata","Manem", email = "mail2mvskumar@gmail.com", 
    role = c("aut")),
  person("Petr","Smirnov", email = "petr.smirnov@uhnresearch.ca", 
    role = c("aut")),
  person("Ian","Smith", email = "ianc.smith@mail.utoronto.ca", 
    role = c("aut")),
  person("Meghan","Lambie", email = "megan.lambie@mail.utoronto.ca", 
    role = c("aut")),
  person("Christopher","Eeles", email = "christopher.eeles@uhnresearch.ca",
    role = c("aut")),
  person("Scott", "Bratman", email = "scott.bratman@rmp.uhn.ca", 
    role = c("aut")),
  person("Benjamin","Haibe-Kains", email = "benjamin.haibe.kains@utoronto.ca",
    role = c("aut","cre"))
  )

Computational tool box for radio-genomic analysis which integrates
    radio-response data, radio-biological modelling and comprehensive cell line
    annotations for hundreds of cancer cell lines. The 'RadioSet' class enables
    creation and manipulation of standardized datasets including information
    about cancer cells lines, radio-response assays and dose-response indicators. 
    Included methods allow fitting and plotting dose-response data using 
    established radio-biological models along with quality control to validate
    results. Additional functions related to fitting and plotting dose response 
    curves, quantifying statistical correlation and calculating area under the
    curve (AUC) or survival fraction (SF) are included. For more details please 
    see the included documentation, references, as well as:
    Manem, V. et al (2018) <doi:10.1101/449793>.