NEWS

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Ravages 1.2.0 (2026-02-27)

• The RAVA-FIRST pipeline is now available for data in build 38. Please check the *build* argument.
• CADD regions and corresponding information is available at https://lysine.univ-brest.fr/RAVA-FIRST/

Ravages 1.1.4

• Fix multiple mistakes in the package
• Addition of a running example for RAVA-FIRST

Ravages 1.1.0 (2022-06-01)

• RAVA-FIRST: *Indels are now considered when computed the median adjusted CADD scores in each CADD region *Indels can be annotated and analysed using the RAVA-FIRST strategy

Ravages 1.0.0 (2021-10-19)

• Analysis using the RAVA-FIRST stratgey by CADD regions: *Used RAVA.FIRST() to run the whole RAVA-FIRST strategy *Three files with adjusted CADD scores, CADD regions and Functional categories are available at https://lysine.univ-brest.fr/RAVA-FIRST/ and directly downoladed in Ravages repository if RAVA-FIRST functions are used *Variants can be annotated into CADD regions and genomic categories (set.CADDregions) *Possilibity to annotate variants with the adjusted CADD score and to filter them based on the median observed in each CADD region (filter.adjustedCADD) *Possibility to perform burden tests with subscores in the regression to take into account the genomic categories (burden.subscores)
• Parallelisation of burden on continuous phenotypes
• get.effect.size replaces get.OR.values in burden() and enables to get the beta estimate for continuous phenotypes
• Add the possibility to filter genomic regions based on the cumulative MAF (min.cumulative.maf)
• Simulations: *random.bed.matrix() is now rbm.GRR() *rbm.haplos.power() and rbm.GRR.power() are available to directly compute power of CAST, WSS and SKAT on the corresponding simulations *CAST power can be computed using theoretical computations in rbm.GRR.power()

Ravages 0.1.5 (2021-05-12)

• Fix bugs with tinythreads and RcppParallel in SKAT

Ravages 0.1.2 (2021-03-16)

• Parallelisation of SKAT on continuous phenotypes
• Minor bugs corrected :
• SKAT() with continuous phenotypes can be run only if at least 2 variants in the genomic region
• Cleaning temporary files in functions called by mclapply to optimise memory usage
• Checks added in multiple functions to verify the fit between functions and arguments