knitr, rmarkdown, lattice, mstate, testthat

stats, survival, DiagrammeR, DiagrammeRsvg, rsvg

stats, survival, DiagrammeR, DiagrammeRsvg, rsvg, mgcv

Contextualization and Evaluation of COI-5P Barcode Data
Designed for the cleaning, contextualization and assessment of cytochrome c oxidase I DNA barcode data (COI-5P, or the five prime portion of COI).
It contains functions for placing COI-5P barcode sequences into a common reading frame, translating DNA sequences to amino acids and for assessing
the likelihood that a given barcode sequence includes an insertion or deletion error. The error assessment relies on the comparison of input sequences
against nucleotide and amino acid profile hidden Markov models (for details see Durbin et al. 1998, ISBN: 9780521629713) trained on a taxonomically
diverse set of reference sequences. The functions are provided as a complete pipeline and are also available individually for efficient and targeted
analysis of barcode data.

Designed for the cleaning, contextualization and assessment of cytochrome c
oxidase I DNA barcode data (COI-5P, or the five prime portion of COI). It contains
functions for placing COI-5P barcode sequences into a common reading frame,
translating DNA sequences to amino acids and for assessing the likelihood that a
given barcode sequence includes an insertion or deletion error. The error assessment
relies on the comparison of input sequences against nucleotide and amino acid profile
hidden Markov models (PHMMs) (for details see Durbin et al. 1998, ISBN: 9780521629713)
trained on a taxonomically diverse set of reference sequences. The functions are
provided as a complete pipeline and are also available individually for efficient and
targeted analysis of barcode data.

Conditional Inference Procedures in a Permutation Test Framework
Torsten Hothorn and Kurt Hornik, with contributions by
Mark van de Wiel and Achim Zeileis
Conditional inference procedures for the general independence
problem including two-sample, K-sample, correlation, censored, ordered and
multivariate problems.
R (>= 2.0.0), methods, survival, mvtnorm