Random Sampling Distribution C++ Routines for Armadillo
c(person("James", "Balamuta", email = "balamut2@illinois.edu", role = c("aut", "cre")),
person("Steven", "Culpepper", email = "sculpepp@illinois.edu", role = c("ctb")))
Provides popular sampling distributions C++ routines based in
armadillo through a header file approach.
James Balamuta [aut, cre],
Steven Culpepper [ctb]

person("Jeremy", "Schwartzentruber", email = "jeremy37@gmail.com", role = c("aut", "cre"))
The R package for GenIE analysis is designed to analyze the next-generation sequencing
output from a set of GenIE experimental replicates. GenIE (genome-editing interrogation of enhancers)
is an experimental method to evaluate the effects of individual single-nucleotide polymorphisms (SNPs)
on gene transcription. It is based on targeted CRISPR-Cas9 genome editing in cultured cells to
produce indels at a target locus, optionally with a homology-dependent recombination (HDR) construct
to create precisely defined genomic changes. Following this, both genomic DNA (gDNA) and RNA are
extracted from the same pool of cells, then complementary DNA (cDNA) is generated from the RNA. Both
gDNA and cDNA are amplified with locus-specific PCR primers, in multiple replicates, and libraries of
the experimental replicates are prepared for next-generation sequencing. The sequencing data from each
replicate for each region should be aligned to either the full reference genome or to a locus-specific
(amplicon) reference genome for analysis by 'rgenie'.

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More information: <https://docs.genius.com/> .
dplyr, purrr, stringr, httr, rvest, foreach, tibble, parallel,
doParallel

R version of GENetic Optimization Using Derivatives
Walter R. Mebane, Jr. <wrm1@cornell.edu>,
Jasjeet Singh Sekhon <jsekhon@fas.harvard.edu>
A genetic algorithm plus derivative optimizer

Walter R. Mebane, Jr. <wrm1@cornell.edu>,
Jasjeet Singh Sekhon <jasjeet_sekhon@harvard.edu>