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- David H Alexander, John Novembre, Kenneth Lange
- Genome research
- 2009

Population stratification has long been recognized as a confounding factor in genetic association studies. Estimated ancestries, derived from multi-locus genotype data, can be used to perform a statistical correction for population stratification. One popular technique for estimation of ancestry is the model-based approach embodied by the widely applied… (More)

Most problems in frequentist statistics involve optimization of a function such as a likelihood or a sum of squares. EM algorithms are among the most effective algorithms for maximum likelihood estimation because they consistently drive the likelihood uphill by maximizing a simple surrogate function for the loglikelihood. Iterative optimization of a… (More)

- Tong Tong Wu, Yi Fang Chen, Trevor J. Hastie, Eric M. Sobel, Kenneth Lange
- Bioinformatics
- 2009

MOTIVATION
In ordinary regression, imposition of a lasso penalty makes continuous model selection straightforward. Lasso penalized regression is particularly advantageous when the number of predictors far exceeds the number of observations.
METHOD
The present article evaluates the performance of lasso penalized logistic regression in case-control disease… (More)

- Eric Sobel, Jeanette C Papp, Kenneth Lange
- American journal of human genetics
- 2002

Detection of genotyping errors and integration of such errors in statistical analysis are relatively neglected topics, given their importance in gene mapping. A few inopportunely placed errors, if ignored, can tremendously affect evidence for linkage. The present study takes a fresh look at the calculation of pedigree likelihoods in the presence of… (More)

Imposition of a lasso penalty shrinks parameter estimates toward zero and performs continuous model selection. Lasso penalized regression is capable of handling linear regression problems where the number of predictors far exceeds the number of cases. This paper tests two exceptionally fast algorithms for estimating regression coefficients with a lasso… (More)

- David H. Alexander, Kenneth Lange
- BMC Bioinformatics
- 2011

The estimation of individual ancestry from genetic data has become essential to applied population genetics and genetic epidemiology. Software programs for calculating ancestry estimates have become essential tools in the geneticist's analytic arsenal. Here we describe four enhancements to ADMIXTURE, a high-performance tool for estimating individual… (More)

- Jeffrey A. Fessler, Edward P. Ficaro, Neal H. Clinthorne, Kenneth Lange
- IEEE Trans. Med. Imaging
- 1997

This paper presents a new class of algorithms for penalized-likelihood reconstruction of attenuation maps from low-count transmission scans. We derive the algorithms by applying to the transmission log-likelihood a version of the convexity technique developed by De Pierro for emission tomography. The new class includes the single-coordinate ascent (SCA)… (More)

- Kenneth Lange, Jeffrey A. Fessler
- IEEE Trans. Image Processing
- 1995

This paper reviews and compares three maximum likelihood algorithms for transmission tomography. One of these algorithms is the EM algorithm, one is based on a convexity argument devised by De Pierro (see IEEE Trans. Med. Imaging, vol.12, p.328-333, 1993) in the context of emission tomography, and one is an ad hoc gradient algorithm. The algorithms enjoy… (More)

- Rita M Cantor, Kenneth Lange, Janet S Sinsheimer
- American journal of human genetics
- 2010

Genome-wide association studies (GWAS) have rapidly become a standard method for disease gene discovery. A substantial number of recent GWAS indicate that for most disorders, only a few common variants are implicated and the associated SNPs explain only a small fraction of the genetic risk. This review is written from the viewpoint that findings from the… (More)

- Hua Zhou, Mary E. Sehl, Janet S. Sinsheimer, Kenneth Lange
- Bioinformatics
- 2010

MOTIVATION
This article extends our recent research on penalized estimation methods in genome-wide association studies to the realm of rare variants.
RESULTS
The new strategy is tested on both simulated and real data. Our findings on breast cancer data replicate previous results and shed light on variant effects within genes.
AVAILABILITY
Rare variant… (More)