Charles Kooperberg - Software


Charles Kooperberg | Home | Pictures | Software | Publications | clk@fredhutch.org
See also Mike LeBlanc's software page for software related to some joint projects.

Genetic association studies

Code for fitting an ultra-sparse variational Bayes spike regression model, with applications to Genome-wide association studies (vBsr) is here. WARNING: Code is in an early release form (version 0.0.1), and details of the model are forthcoming. Email questions to Ben Logsdon (blogsdon@u.washington.edu).

Code for approximate power calculations for identification of gene x gene and gene x environment interactions in genomewide association studies using a two-stage analysis. Download the package powerGWASinteraction from CRAN.

Code for Adaptively Weighted Association Statistics is here. This is software written by Mike LeBlanc mleblanc@fhcrc.org that implements adaptive selection and weighting to potentially improve the power of association testing of genetic factors with disease outcome. Code for SNP-Haplotype Adaptive Regression (SHARE) to perform multi-locus analysis in order to account for LD patterns observed in human genome developed by James Dai jdai@scharp.org is available in the package SHARE from CRAN. Code for semiparametric estimation exploiting covariate independence in two-phase randomized trials developed by James Dai jdai@scharp.org is available in the package TwoPhaseInd from CRAN.
Software that was supported in part by ENDGAME (Enhancing Development of Genome-wide Association Methods) project U01 CA 125489 Dissecting complex traits with diverse resources. Investigators on this project were James Dai, Li Hsu, Charles Kooperberg, Michael LeBlanc, Hua Tang, and Yingye Zheng.


Logic Regression

Logic Regression.
Logic Regression: R libraries to fit logic regression models.


Microarrays

Improved background correction for spotted DNA microarrays: R code. It is also implemented in Gordon Smyth's Limma package on bioconductor as the function kooperberg.

Directed indices for exploring gene expression data: code is here. (Code written by Mike Leblanc mleblanc@fhcrc.org.)

Extreme regression code is here. (Code written by Mike Leblanc mleblanc@fhcrc.org.)


Polynomial Splines

Libraries

Software for hare, heft, lspec, logspline, polyclass and polymars, as well as the logspline version discussed in Stone et al (1997) are now available as an R-package. You can download the package polspline from CRAN. (Version 1.0.11, 5/24/2005.)

Software for logspline as well as the logspline version discussed in Stone et al (1997) are now available as an R-package. You can download the package logspline from CRAN. (Version 2,9,2, 4/18/2005.) The latest version of logspline is always part of the latest version of polspline .

A book about splines

Statistical Modeling with Spline Functions, an unfinished, incomplete, monograph.

Individual programs

I suggest downloading polspline (see above), it will give you all programs at once. The programs on this page were last updated 03/10/2005. The programs on statlib are no longer updated.

POLYCLASS.
Polyclass: S functions to estimate conditional class probabilities based on a discrete response variable and a number of predictors. tar.gz archive.
I suggest downloading polspline (see above), it will give you all programs at once.

POLYMARS.
Polymars: A set of S functions for classification and (polychotomous) regression using adaptively selected polynomial splines for the model building. (Written by Martin O'Connor under my direction.)
I suggest downloading polspline (see above), it will give you all programs at once.

HARE.
Hazard Regression: S functions to estimate the conditional log-hazard function based on possibly censored data and covariates and obtain corresponding densities, hazard rates, probabilities, quantiles and random samples. Includes proportional hazard model as special case.
I suggest downloading polspline (see above), it will give you all programs at once.

HEFT.
Hazard Estimation with Flexible Tails: S functions to estimate an unknown hazard function based on possibly censored data and obtain corresponding densities probabilities, quantiles and random samples.
I suggest downloading polspline (see above), it will give you all programs at once.

LOGSPLINE. There are two versions of this software. LSPEC.
Logspline estimation of a possibly mixed spectral distribution: S functions to estimate the spectral density, line spectrum and spectral distribution based on time series data.
I suggest downloading polspline (see above), it will give you all programs at once.