DWD implementation based on A IPM SOCP solver
Hanwen Huang, Perry Haaland, Xiaosun Lu, Yufeng Liu, J. S. Marron
This package provides the implementation of distance weighted discrimination (DWD) using an interior point
method for the solution of second order cone programming problems, originally described by K.C. Toh, M.J. Todd,
R.H. Tutuncu (1999).

Hanwen Huang, Perry Haaland, Xiaosun Lu, Yufeng Liu, J. S.
Marron
This package provides the implementation of distance
weighted discrimination (DWD) using an interior point method
for the solution of second order cone programming problems,
originally described by K.C. Toh, M.J. Todd, R.H. Tutuncu
(1999).

Fast Algorithms for Large Scale Generalized Distance Weighted
Discrimination
Xin-Yee Lam, J.S. Marron, Defeng Sun, and Kim-Chuan Toh
Solving large scale distance weighted discrimination.
The main algorithm is a symmetric Gauss-Seidel based alternating direction method of multipliers (ADMM) method. See Lam, X.Y., Marron, J.S., Sun, D.F., and Toh, K.C. (2018) <arXiv:1604.05473> for more details.

Gene Expression Deconvolution Using Dampened Weighted Least
Squares
c(person("Daphne", "Tsoucas", email = "dtsoucas@gmail.com", role = "aut"),
person("Adriana", "Sistig", email = "adriana.sistig@icahn.mssm.edu",
role = c("aut","cre")))
The rapid development of single-cell transcriptomic technologies
has helped uncover the cellular heterogeneity within cell populations.
However, bulk RNA-seq continues to be the main workhorse for quantifying
gene expression levels due to technical simplicity and low cost. To most
effectively extract information from bulk data given the new knowledge
gained from single-cell methods, we have developed a novel algorithm to
estimate the cell-type composition of bulk data from a single-cell
RNA-seq-derived cell-type signature. Comparison with existing methods using
various real RNA-seq data sets indicates that our new approach is more
accurate and comprehensive than previous methods, especially for the
estimation of rare cell types. More importantly,our method can detect
cell-type composition changes in response to external perturbations,
thereby providing a valuable, cost-effective method for dissecting the
cell-type-specific effects of drug treatments or condition changes.
As such, our method is applicable to a wide range of biological and
clinical investigations. Dampened weighted least squares ('DWLS') is an
estimation method for gene expression deconvolution, in which the cell-type
composition of a bulk RNA-seq data set is computationally inferred.
This method corrects common biases towards cell types that are
characterized by highly expressed genes and/or are highly prevalent, to
provide accurate detection across diverse cell types. See:
<https://www.nature.com/articles/s41467-019-10802-z.pdf> for more
information about the development of 'DWLS' and the methods behind our
functions.
quadprog, reshape, Seurat, ROCR, varhandle, dplyr, stats,
utils, e1071, MAST, SummarizedExperiment
Daphne Tsoucas [aut],
Adriana Sistig [aut, cre]