Packaged: 2022-06-01 14:24:30 UTC; morenobevilacqua

Depends: R (>= 4.0.5), GPvecchia,fields, mapproj, shape, codetools
Packaged: 2022-08-25 14:53:14 UTC; victormorales

Depends: R (>= 4.1.0), GPvecchia,fields, mapproj, shape, codetools
Packaged: 2022-10-22 22:13:13 UTC; victormorales

Packaged: 2022-11-30 01:08:24 UTC; victormorales

Title: Geospatial Queries Using 'PyMongo'
Description: Utilizes methods of the 'PyMongo' 'Python' library to initialize, insert and query 'GeoJson' data (see <https://api.mongodb.com/python/current/#> for more information on 'PyMongo'). Furthermore, it allows the user to validate 'GeoJson' objects and to use the console for 'MongoDB' (bulk) commands. The 'reticulate' package provides the 'R' interface to 'Python' modules, classes and functions.
SystemRequirements: MongoDB (>= 3.4.0), Python (>= 2.7). Installation
instructions and links can be found in the README file.
Imports: reticulate, R6, geojsonR, data.table

Description: Utilizes methods of the 'PyMongo' 'Python' library to initialize, insert and query 'GeoJson' data (see <https://github.com/mongodb/mongo-python-driver> for more information on 'PyMongo'). Furthermore, it allows the user to validate 'GeoJson' objects and to use the console for 'MongoDB' (bulk) commands. The 'reticulate' package provides the 'R' interface to 'Python' modules, classes and functions.

Title: Calculating Geographic Range from Occurrence Data
Description: Calculates and analyzes six measures of geographic range from a set of longitudinal and latitudinal occurrence data. Measures included are minimum convex hull area, minimum spanning tree distance, longitudinal range, latitudinal range, maximum pairwise great circle distance, and number of X by X degree cells occupied.
Author: James Boyle Developer [aut, cre]
Maintainer: James Boyle Developer <jamesboy@buffalo.edu>

Title: Processed a various types of data on GEO and TCGA
Authors@R: person(given = "Erqiang", family = "Hu", email = "13766876214@163.com", role  = c("aut", "cre"))
Description: Gene Expression Omnibus(GEO) and The Cancer Genome Atlas (TCGA)
provide us with a wealth of data, such as RNA-seq, DNA Methylation,
and Copy number variation data. It's easy to download data from TCGA using the
gdc tool, but processing these data into a format suitable for bioinformatics
analysis requires more work. This R package was developed to handle these data.
Suggests: knitr, rmarkdown, DESeq2, S4Vectors
Packaged: 2019-09-10 03:25:39 UTC; Administrator