Sequential Experimental Design via Matching on-the-Fly
c(
person("Adam", "Kapelner", email = "kapelner@qc.cuny.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5985-6792")),
person("Abba", "Krieger", email = "krieger@wharton.upenn.edu", role = "aut")
)
Generates the following sequential two-arm experimental designs:
(1) completely randomized (Bernoulli)
(2) balanced completely randomized
(3) Efron's (1971) Biased Coin
(4) Atkinson's (1982) Covariate-Adjusted Biased Coin
(5) Kapelner and Krieger's (2014) Covariate-Adjusted Matching on the Fly
(6) Kapelner and Krieger's (2021) CARA Matching on the Fly with Differential Covariate Weights (Naive)
(7) Kapelner and Krieger's (2021) CARA Matching on the Fly with Differential Covariate Weights (Stepwise)
and also provides the following types of inference:
(1) estimation (with both Z-style estimators and OLS estimators),
(2) frequentist testing (via asymptotic distribution results and via employing the nonparametric randomization test) and
(3) frequentist confidence intervals (only under the superpopulation sampling assumption currently). Details can be found
in our publication: Kapelner and Krieger "A Matching Procedure for Sequential Experiments that Iteratively Learns which
Covariates Improve Power" (2020) <arXiv:2010.05980>.
Adam Kapelner [aut, cre] (<https://orcid.org/0000-0001-5985-6792>),
Abba Krieger [aut]

Calculates possible epitopes and co-mutations
Package includes functions to analyse sequence data in FASTA Format with known HLA types or other features and calculate in the case of HLA as feature possible epitopes from them. Further it calculates possible co-mutations from these sequences and generates graphical output in PDF.

A Tool to Associate FASTA Sequences and Features
SeqFeatR provides user friendly methods for the identification of sequence patterns that are statistically significantly associated with a property of the sequence. For instance, SeqFeatR allows to identify viral immune escape mutations for hosts of given HLA types. The underlying statistical method is Fisher's exact test, with appropriate corrections for multiple testing. Patterns may be point mutations or n-tuple of mutations. SeqFeatR offers several ways to visualize the results of the statistical analyses.