Title: Analyze Circulating Tumor DNA Sequencing Data
Description: Contains tools to analyze minimal residual disease and cell-free DNA fragmentation from aligned sequencing data.
More details on the methods can be found in:
Amjad Alkodsi, Leo Meriranta, Annika Pasanen, Sirpa Leppä (2020) <doi:10.1101/2020.01.27.912790>.
Imports: magrittr, dplyr (>= 0.8.3), tidyr (>= 1.0.0), purrr (>=
GenomicRanges, IRanges, GenomeInfoDb, BiocGenerics, BSgenome,
GenomicAlignments, rlang (>= 0.4.0), Biostrings, methods, furrr
Suggests: BSgenome.Hsapiens.UCSC.hg19, testthat (>= 2.1.0), ggplot2,
Author: Amjad Alkodsi [aut, cre] (<https://orcid.org/0000-0003-3528-4683>)

Title: Contingency Table Analysis Based on ML Fitting of MPH Models
Authors@R: c(person("Joseph B.", "Lang", role = "aut",
person("Qiansheng", "Zhu", role = c("aut", "cre"),
Imports: intervals, numDeriv, limSolve, methods
Description: Contingency table analysis is performed based on maximum likelihood (ML) fitting of
multinomial-Poisson homogeneous (MPH) and homogeneous linear predictor (HLP) models.
for MPH and HLP models. Objects computed include model goodness-of-fit statistics; likelihood-
based (cell- and link-specific) residuals; and cell probability and expected count estimates along
with standard errors. This package can also compute test-inversion--e.g. Wald, profile likelihood,
score, power-divergence--confidence intervals for contingency table estimands, when table
probabilities are potentially subject to equality constraints. For test-inversion intervals, see
Packaged: 2021-08-22 01:16:52 UTC; QianshengZhu

Title: A Procedure to Clean, Decompose and Aggregate Timeseries
Authors@R: person("Francois", "Ritter", email = "ritter.francois@gmail.com", role = c("cre","aut"),comment = c(ORCID = "0000-0001-6123-2145"))
Description: Clean, decompose and aggregate univariate time series following the procedure "Cyclic/trend decomposition using bin interpolation" and the Logbox method for flagging outliers, both detailed in Ritter, F.: Technical note: A procedure to clean, decompose and aggregate time series, Hydrol. Earth Syst. Sci. Discuss. [preprint], <doi:10.5194/hess-2021-609>, in review.
Packaged: 2022-03-08 11:02:42 UTC; Utilisateur
Author: Francois Ritter [cre, aut] (<https://orcid.org/0000-0001-6123-2145>)