Title: High Throughput Sequencing of Stable Isotope Probing Data
person("Nicholas", "Youngblut", email="nyoungb2@gmail.com", role=c("aut", "cre")),
Description: Perform HTS-SIP analyses such as high resolution stable isotope probing (HR-SIP),
multi-window high resolution stable isotope probing (MW-HR-SIP), and quantitative stable
isotope probing (q-SIP). More information on HR-SIP, MW-HR-SIP, and q-SIP can be
1) Pepe-Ranney, Charles, Ashley N. Campbell, Chantal N. Koechli, Sean Berthrong, and
Daniel H. Buckley. 2016. "Unearthing the Ecology of Soil Microorganisms Using a
High Resolution DNA-SIP Approach to Explore Cellulose and Xylose Metabolism in
Soil." Terrestrial Microbiology, 703. <doi:10.3389/fmicb.2016.00703>
2) Youngblut, Nicholas D., and Daniel H. Buckley. "Evaluating the Accuracy of DNA
3) Hungate, Bruce A., Rebecca L. Mau, Egbert Schwartz, J. Gregory Caporaso,
Paul Dijkstra, Natasja van Gestel, Benjamin J. Koch, et al. 2015. "Quantitative
Microbial Ecology Through Stable Isotope Probing." Applied and Environmental
Imports: magrittr (>= 1.5), stringr (>= 1.0.0), plyr (>= 1.8.4), dplyr
Suggests: testthat, knitr, rmarkdown, doParallel

Description: Functions for analyzing high throughput sequencing
Analyses include high resolution stable isotope probing (HR-SIP),
multi-window high resolution stable isotope probing (MW-HR-SIP),
and quantitative stable isotope probing (q-SIP).

Imports: igraph(>= 1.0.1), ape(>= 4.1), magrittr (>= 1.5), stringr (>=
phyloseq (>= 1.19.1), coenocliner (>= 0.2.2), lazyeval(>=

person("Samuel", "Barnett", email="seb369@cornell.edu", role=c("cre", "ctb"))

Imports: igraph(>= 1.1.2), ape(>= 4.1), magrittr (>= 1.5), stringr (>=
phyloseq (>= 1.20.0), coenocliner (>= 0.2.2), lazyeval(>=

Packaged: 2019-09-13 20:09:39 UTC; sambarnett

Title: compute HUM value and visualize ROC curves
Author: Natalia Novoselova,Junxi Wang,Jialiang Li, Frank Pessler,Frank Klawonn
Description: Tools for computing HUM (Hypervolume Under the Manifold) value to estimate features ability
to discriminate the class labels, visualizing the ROC curve for two or three class labels.