Statistical Analyses of De Novo Genetic Variants

An integrated toolset for the analysis of de novo (sporadic) genetic sequence variants. denovolyzeR implements a mutational model that estimates the probability of a de novo genetic variant arising in each human gene, from which one can infer the expected number of de novo variants in a given population size. Observed variant frequencies can then be compared against expectation in a Poisson framework. denovolyzeR provides a suite of functions to implement these analyses for the interpretation of de novo variation in human disease.


Release Notes

denovolyzeR 0.2.0

  • Fixed a critical bug, whereby denovolyzeByGenes() returned incorrect output if user overrode default variant classes analysed (using includeClasses argument; column labels did not match data content)
  • Updated underlying dependency from reshape to reshape2
  • Changed output format so that all data is returned in columns. Previously either "gene" or "class" was returned as rownames of the output data structure.

denovolyzeR 0.1.1

  • Correct minor errors in vignette
  • Provide citation
  • Address compatibility with updated dplyr 0.5.0

denovolyzeR 0.1.0

  • This is the first release of denovolyzeR to CRAN

pre-release builds (

  • 2015-04-01: v0.0.0.9003
    new functionality includes analysis of sub-types of missense variation
    argument names and output formats are about to change: this development release serves to preserce a working version of the package using first draft argument names

  • 2014-11-11: v0.0.0.9000 core statistical functionality is complete and ready for beta-testing
    main limitation is a lack of error-catching
    there may also be very minor modifications to underlying probability tables

Reference manual

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0.2.0 by James Ware, 5 years ago

Report a bug at

Browse source code at

Authors: James Ware [aut, cre] , Jason Homsy [ctb] , Kaitlin Samocha [ctb]

Documentation:   PDF Manual  

GPL-3 license

Imports dplyr, reshape2

Suggests knitr, rmarkdown

See at CRAN