Genetics and Genomics Commons^™

Effect Of Misreported Family History On Mendelian Mutation Prediction Models, Hormuzd A. Katki

Johns Hopkins University, Dept. of Biostatistics Working Papers

People with familial history of disease often consult with genetic counselors about their chance of carrying mutations that increase disease risk. To aid them, genetic counselors use Mendelian models that predict whether the person carries deleterious mutations based on their reported family history. Such models rely on accurate reporting of each member's diagnosis and age of diagnosis, but this information may be inaccurate. Commonly encountered errors in family history can significantly distort predictions, and thus can alter the clinical management of people undergoing counseling, screening, or genetic testing. We derive general results about the distortion in the carrier probability estimate …

Accuracy Of Msi Testing In Predicting Germline Mutations Of Msh2 And Mlh1: A Case Study In Bayesian Meta-Analysis Of Diagnostic Tests Without A Gold Standard, Sining Chen, Patrice Watson, Giovanni Parmigiani

Johns Hopkins University, Dept. of Biostatistics Working Papers

Microsatellite instability (MSI) testing is a common screening procedure used to identify families that may harbor mutations of a mismatch repair gene and therefore may be at high risk for hereditary colorectal cancer. A reliable estimate of sensitivity and specificity of MSI for detecting germline mutations of mismatch repair genes is critical in genetic counseling and colorectal cancer prevention. Several studies published results of both MSI and mutation analysis on the same subjects. In this article we perform a meta-analysis of these studies and obtain estimates that can be directly used in counseling and screening. In particular we estimate the …

A Model Based Background Adjustment For Oligonucleotide Expression Arrays, Zhijin Wu, Rafael A. Irizarry, Robert Gentleman, Francisco Martinez Murillo, Forrest Spencer

Johns Hopkins University, Dept. of Biostatistics Working Papers

High density oligonucleotide expression arrays are widely used in many areas of biomedical research. Affymetrix GeneChip arrays are the most popular. In the Affymetrix system, a fair amount of further pre-processing and data reduction occurs following the image processing step. Statistical procedures developed by academic groups have been successful at improving the default algorithms provided by the Affymetrix system. In this paper we present a solution to one of the pre-processing steps, background adjustment, based on a formal statistical framework. Our solution greatly improves the performance of the technology in various practical applications.

Affymetrix GeneChip arrays use short oligonucleotides to …

Optimal Sample Size For Multiple Testing: The Case Of Gene Expression Microarrays, Peter Muller, Giovanni Parmigiani, Christian Robert, Judith Rousseau

Johns Hopkins University, Dept. of Biostatistics Working Papers

We consider the choice of an optimal sample size for multiple comparison problems. The motivating application is the choice of the number of microarray experiments to be carried out when learning about differential gene expression. However, the approach is valid in any application that involves multiple comparisons in a large number of hypothesis tests. We discuss two decision problems in the context of this setup: the sample size selection and the decision about the multiple comparisons. We adopt a decision theoretic approach,using loss functions that combine the competing goals of discovering as many ifferentially expressed genes as possible, while keeping …