person("Pablo", "Pagnone", role = c("aut", "cre"), email = "pablodp84@gmail.com"),
person("Aleksander", "Dietrichson", role = c("aut"), email = "dietrichson@gmail.com")
Imports: shiny, yaml, config, shinyjs, httr, dplyr, base64enc,

Title: Data Source Agnostic Filtering Tools
Description: Common API for filtering data stored in different data models.
Provides multiple filter types and reproducible R code.
Works standalone or with 'shinyCohortBuilder' as the GUI for interactive Shiny apps.
Imports: yaml, jsonlite, purrr, dplyr (>= 1.0.0), tidyr, magrittr,
glue, R6, ggplot2, rlang (>= 1.0), formatR
Suggests: testthat (>= 3.0.0), shiny, knitr, rmarkdown

Description: Functions to simplify the process of preparing event and transaction for cohort analysis.
Imports: data.table, dplyr, dtplyr, magrittr, tibble, tidyr, zoo
Packaged: 2021-07-07 22:35:18 UTC; peerchristensen

Packaged: 2022-05-15 21:55:11 UTC; peerchristensen

Imports: stats, epitools, survival, DiagrammeR, DiagrammeRsvg, rsvg
Suggests: knitr, rmarkdown, ggplot2, lattice, mstate
Description: Functions to make lifetables and to calculate hazard function estimate using Poisson regression model with splines. Includes function to draw simple flowchart of cohort study. Function boxesLx() makes boxes of transition rates between states. It utilizes 'Epi' package 'Lexis' data.

Depends: R (>= 3.6), Epi, cmprsk, ggplot2
Suggests: knitr, rmarkdown, lattice, mstate, testthat

Imports: stats, survival, DiagrammeR, DiagrammeRsvg, rsvg

Imports: stats, survival, DiagrammeR, DiagrammeRsvg, rsvg, mgcv

Title: Contextualization and Evaluation of COI-5P Barcode Data
Maintainer: Cameron M. Nugent <nugentc@uoguelph.ca>
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