BART, boot, gbm, ggplot2, metR, pryr, stats, twang, tidyr

Wrangle, Analyze, and Visualize Animal Movement Data
c(person(given = "Vikram B.",
family = "Baliga",
role = c("aut", "cre"),
email = "vbaliga87@gmail.com",
comment = c(ORCID = "0000-0002-9367-8974")),
person(given = "Melissa S.",
family = "Armstrong",
role = "aut",
email = "melissa.armstrong@gmail.com",
comment = c(ORCID = "0000-0002-3059-0094")),
person(given = "Eric R.",
family = "Press",
role = "aut",
email = "epress12@gmail.com",
comment = c(ORCID = "0000-0002-1944-3755")),
person(given = "Anne-Sophie",
family = "Bonnet-Lebrun",
role = "rev"),
person(given = "Marco",
family = "Sciaini",
role = "rev")
)
Tools to import, clean, and visualize movement data,
particularly from motion capture systems such as Optitrack's
'Motive', the Straw Lab's 'Flydra', or from other sources. We provide
functions to remove artifacts, standardize tunnel position and tunnel
axes, select a region of interest, isolate specific trajectories, fill
gaps in trajectory data, and calculate 3D and per-axis velocity. For
experiments of visual guidance, we also provide functions that use
subject position to estimate perception of visual stimuli.
Vikram B. Baliga [aut, cre] (<https://orcid.org/0000-0002-9367-8974>),
Melissa S. Armstrong [aut] (<https://orcid.org/0000-0002-3059-0094>),
Eric R. Press [aut] (<https://orcid.org/0000-0002-1944-3755>),
Anne-Sophie Bonnet-Lebrun [rev],
Marco Sciaini [rev]

R.matlab, data.table (>= 1.12.2), magrittr (>= 1.5), dplyr (>=
1.0.0), stringr (>= 1.4.0), tibble (>= 3.0.1), tidyr (>=
1.1.0), fANCOVA, purrr (>= 0.3.3), ggplot2 (>= 3.3.0),
tidyselect (>= 1.1.0), cowplot, anomalize, lubridate

R.matlab, data.table (>= 1.12.2), magrittr (>= 1.5), dplyr (>=
1.0.0), stringr (>= 1.4.0), tibble (>= 3.0.1), tidyr (>=
1.1.0), fANCOVA, purrr (>= 0.3.3), ggplot2 (>= 3.4.0),
tidyselect (>= 1.1.0), cowplot, anomalize, lubridate

c(person(given = "Junwei", family = "Han", email = "hanjunwei1981@163.com", role  = c("aut", "cre", "cph")),
person(given = "Xiangmei", family = "Li", role  = "aut"))
A systematic bioinformatics tool to develop a new pathway-based gene panel for tumor mutational burden (TMB) assessment (pathway-based tumor mutational burden, PTMB), using somatic mutations files in an efficient manner from either The Cancer Genome Atlas sources or any in-house studies as long as the data is in mutation annotation file (MAF) format. Besides, we develop a multiple machine learning method using the sample's PTMB profiles to identify cancer-specific dysfunction pathways, which can be a biomarker of prognostic and predictive for cancer immunotherapy.
maftools, clusterProfiler, BiocGenerics, GenomicFeatures,
purrr, utils, glmnet, randomForest, stats, survival, survminer,
caret, data.table, RColorBrewer, grDevices, pROC, graphics
stringi, knitr, rmarkdown, testthat, BiocManager, xfun,
e1071, qpdf, tinytex, spelling
Junwei Han [aut, cre, cph],
Xiangmei Li [aut]