Title: Implementation of SparseDC Algorithm
person("Jun", "Li", email = "jun.li@nd.edu",role = c("aut","cre")),
person("Martin", "Barron", email = "mbarron2@nd.edu",role = c("aut")))
Description: Implements the algorithm described in
Barron, M., Zhang, S. and Li, J. "A sparse differential
clustering algorithm for tracing cell type changes via single-cell
RNA-sequencing data"  (Unpublished). This algorithm clusters samples from two different
populations, links the clusters across the conditions and identifies
marker genes for these changes. The package was designed for scRNA-Seq
data but is also applicable to many other data types, just replace cells
with samples and genes with variables. The package also contains functions
for estimating the parameters for SparseDC as outlined in the paper.
Packaged: 2017-09-17 15:58:36 UTC; Administrator

Packaged: 2017-10-10 14:13:34 UTC; Administrator

Barron, M., Zhang, S. and Li, J. 2017, "A sparse differential
RNA-sequencing data", Nucleic Acids Research, gkx1113,
<doi:10.1093/nar/gkx1113>. This algorithm clusters samples from two
different populations, links the clusters across the conditions and
identifies marker genes for these changes. The package was designed for
scRNA-Seq data but is also applicable to many other data types, just
replace cells with samples and genes with variables. The package also
contains functions for estimating the parameters for SparseDC as outlined
in the paper. We recommend that users further select their marker genes
using the magnitude of the cluster centers.
Packaged: 2018-01-04 17:55:17 UTC; Administrator

Packaged: 2017-05-02 06:32:54 UTC; Administrator

Title: Scaling Count and Binary Data with Sparse Factor Analysis
Author: Marc Ratkovic, In Song Kim, John Londregan, and Yuki Shiraito
Description: Multidimensional scaling provides a means of uncovering a latent structure underlying observed data, while estimating the number of latent dimensions.  This package presents a means for scaling binary and count data, for example the votes and word counts for legislators.  Future work will include an EM implementation and extend this work to ordinal and continuous data.
Imports: Rcpp (>= 0.11.4), MASS, VGAM, truncnorm