The Cancer Genome Atlas (TCGA) is a program aimed at improving our understanding of Cancer Biology. Several TCGA Datasets are available online. 'TCGAretriever' helps accessing and downloading TCGA data hosted on 'cBioPortal' via its Web Interface (see <http://www.cbioportal.org/> for more information). 'TCGAretriever' is easy to use (get all the TCGA data you need with a few lines of code), enforces reliable data download (via 'httr'), and is suitable for downloading large volumes of data.

Client for the Cancer Imaging Archive REST API
person("Pamela", "Russell", email = "pamela.russell@ucdenver.edu", role = c("aut", "cre"))
A wrapper for The Cancer Imaging Archive's REST API. The Cancer
Imaging Archive (TCIA) hosts de-identified medical images of cancer
available for public download, as well as rich metadata for each image
series. TCIA provides a REST API for programmatic access to the data.
This package provides simple functions to access each API endpoint.
For more information, see <https://github.com/pamelarussell/TCIApathfinder>
and TCIA's website.

person("Pamela", "Russell", email = "pamela.russell@gmail.com", role = c("aut", "cre"))

Spacekime Analytics, Time Complexity and Inferential Uncertainty
c(person("Yongkai", "Qiu", role = "aut", email = "yongkai@umich.edu"),
person("Zhe", "Yin", role = "aut"),
person("Jinwen", "Cao", role = "aut"),
person("Yupeng", "Zhang", role = "aut"),
person("Yuyao", "Liu", role = "aut"),
person("Rouben", "Rostamian", role = "ctb"),
person("Ranjan", "Maitra", role = "ctb"),
person("Daniel", "Rowe", role = "ctb"),
person("Daniel", "Adrian", role = "ctb", comment = "gLRT method for complex-valued fMRI statistics"),
person("Yunjie", "Guo", role = c("aut", "cre"), email = "jerryguo@umich.edu"),
person("Ivo","Dinov", role = "aut", email = "statistics@umich.edu"))
Provide the core functionality to transform longitudinal data to
complex-time (kime) data using analytic and numerical techniques, visualize the original
time-series and reconstructed kime-surfaces, perform model based (e.g., tensor-linear regression)
and model-free classification and clustering methods in the book Dinov, ID and Velev, MV. (2021)
"Data Science: Time Complexity, Inferential Uncertainty, and Spacekime Analytics", De Gruyter STEM Series,
ISBN 978-3-11-069780-3. <https://www.degruyter.com/view/title/576646>.
The package includes 18 core functions which can be separated into three groups.
1) draw longitudinal data, such as fMRI time-series, and forecast or transform the time-series data.
2) simulate real-valued time-series data, e.g., fMRI time-courses, detect the activated areas,
report the corresponding p-values, and visualize the p-values in the 3D brain space.
3) Laplace transform and kimesurface reconstructions of the fMRI data.
stats, ggplot2, dplyr, tidyr, RColorBrewer, fancycut, scales,
plotly, gridExtra, ggpubr, ICSNP, AnalyzeFMRI, rrcov, geometry,
DT, forecast, fmri, pracma, zoo, extraDistr, parallel, foreach,
spatstat, cubature, doParallel, reshape2, MultiwayRegression
Yongkai Qiu [aut],
Zhe Yin [aut],
Jinwen Cao [aut],
Yupeng Zhang [aut],
Yuyao Liu [aut],
Rouben Rostamian [ctb],
Ranjan Maitra [ctb],
Daniel Rowe [ctb],
Daniel Adrian [ctb] (gLRT method for complex-valued fMRI statistics),
Yunjie Guo [aut, cre],
Ivo Dinov [aut]