Open Access. Powered by Scholars. Published by Universities.®

Microarrays Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 10 of 10

Full-Text Articles in Microarrays

A Multilevel Model To Address Batch Effects In Copy Number Estimation Using Snp Arrays, Robert B. Scharpf, Ingo Ruczinski, Benilton Carvalho, Betty Doan, Aravinda Chakravarti, Rafael A. Irizarry Jun 2009

A Multilevel Model To Address Batch Effects In Copy Number Estimation Using Snp Arrays, Robert B. Scharpf, Ingo Ruczinski, Benilton Carvalho, Betty Doan, Aravinda Chakravarti, Rafael A. Irizarry

Johns Hopkins University, Dept. of Biostatistics Working Papers

Submicroscopic changes in chromosomal DNA copy number dosage are common and have been implicated in many heritable diseases and cancers. Recent high-throughput technologies have a resolution that permits the detection of segmental changes in DNA copy number that span thousands of basepairs across the genome. Genome-wide association studies (GWAS) may simultaneously screen for copy number-phenotype and SNP-phenotype associations as part of the analytic strategy. However, genome-wide array analyses are particularly susceptible to batch effects as the logistics of preparing DNA and processing thousands of arrays often involves multiple laboratories and technicians, or changes over calendar time to the reagents and …


A Multilevel Model To Address Batch Effects In Copy Number Using Snp Arrays, Robert B. Scharpf, Ingo Ruczinski, Benilton Carvalho, Betty Doan, Aravinda Chakravarti, Rafael A. Irizarry Jun 2009

A Multilevel Model To Address Batch Effects In Copy Number Using Snp Arrays, Robert B. Scharpf, Ingo Ruczinski, Benilton Carvalho, Betty Doan, Aravinda Chakravarti, Rafael A. Irizarry

Johns Hopkins University, Dept. of Biostatistics Working Papers

Submicroscopic changes in chromosomal DNA copy number dosage are common and have been implicated in many heritable diseases and cancers. Recent high-throughput technologies have a resolution that permits the detection of segmental changes in DNA copy number that span thousands of basepairs across the genome. Genome-wide association studies (GWAS) may simultaneously screen for copy number-phenotype and SNP-phenotype associations as part of the analytic strategy. However, genome-wide array analyses are particularly susceptible to batch effects as the logistics of preparing DNA and processing thousands of arrays often involves multiple laboratories and technicians, or changes over calendar time to the reagents and …


Quantifying Uncertainty In Genotype Calls, Benilton Carvalho, Thomas A. Louis, Rafael A. Irizarry Jan 2009

Quantifying Uncertainty In Genotype Calls, Benilton Carvalho, Thomas A. Louis, Rafael A. Irizarry

Johns Hopkins University, Dept. of Biostatistics Working Papers

Genome-wide association studies (GWAS) are used to discover genes underlying complex, heritable disorders for which less powerful study designs have failed in the past. The number of GWAS has skyrocketed recently with findings reported in top journals and the mainstream media. Mircorarrays are the genotype calling technology of choice in GWAS as they permit exploration of more than a million single nucleotide polymorphisms (SNPs)simultaneously. The starting point for the statistical analyses used by GWAS, to determine association between loci and disease, are genotype calls (AA, AB, or BB). However, the raw data, microarray probe intensities, are heavily processed before arriving …


Comparison Of Affymetrix Genechip Expression Measures, Rafael A. Irizarry, Zhijin Wu, Harris A. Jaffee Sep 2005

Comparison Of Affymetrix Genechip Expression Measures, Rafael A. Irizarry, Zhijin Wu, Harris A. Jaffee

Johns Hopkins University, Dept. of Biostatistics Working Papers

Affymetrix GeneChip expression array technology has become a standard tool in medical science and basic biology research. In this system, preprocessing occurs before one obtains expression level measurements. Because the number of competing preprocessing methods was large and growing, in the summer of 2003 we developed a benchmark to help users of the technology identify the best method for their application. In conjunction with the release of a Bioconductor R package (affycomp), a webtool was made available for developers of preprocessing methods to submit them to a benchmark for comparison. There have now been over 30 methods compared via the …


When Should One Substract Background Fluorescence In Two Color Microarrays?, Robert B. Scharpf, Christine A. Iacobuzio-Donahue, Julie B. Sneddon, Giovanni Parmigiani Jul 2005

When Should One Substract Background Fluorescence In Two Color Microarrays?, Robert B. Scharpf, Christine A. Iacobuzio-Donahue, Julie B. Sneddon, Giovanni Parmigiani

Johns Hopkins University, Dept. of Biostatistics Working Papers

Two color microarrays are a powerful tool for genomic analysis, but have noise components that make inferences regarding gene expression inefficient and potentially misleading. Background fluorescence,whether attributable to non-specific binding or other sources,is an important component of noise. The decision to subtract fluorescence surrounding spots of hybridization from spot fluorescence has been controversial, with no clear criteria for determining circumstances that may favor, or disfavor, background subtraction. While it is generally accepted that subtracting background reduces bias but increases variance in the estimates of the ratios of interest, no formal analysis of the bias-variance trade off of background subtraction has …


A Statistical Framework For The Analysis Of Microarray Probe-Level Data, Zhijin Wu, Rafael A. Irizarry Mar 2005

A Statistical Framework For The Analysis Of Microarray Probe-Level Data, Zhijin Wu, Rafael A. Irizarry

Johns Hopkins University, Dept. of Biostatistics Working Papers

Microarrays are an example of the powerful high through-put genomics tools that are revolutionizing the measurement of biological systems. In this and other technologies, a number of critical steps are required to convert the raw measures into the data relied upon by biologists and clinicians. These data manipulations, referred to as preprocessing, have enormous influence on the quality of the ultimate measurements and studies that rely upon them. Many researchers have previously demonstrated that the use of modern statistical methodology can substantially improve accuracy and precision of gene expression measurements, relative to ad-hoc procedures introduced by designers and manufacturers of …


Cross-Study Validation And Combined Analysis Of Gene Expression Microarray Data, Elizabeth Garrett-Mayer, Giovanni Parmigiani, Xiaogang Zhong, Leslie Cope, Edward Gabrielson Dec 2004

Cross-Study Validation And Combined Analysis Of Gene Expression Microarray Data, Elizabeth Garrett-Mayer, Giovanni Parmigiani, Xiaogang Zhong, Leslie Cope, Edward Gabrielson

Johns Hopkins University, Dept. of Biostatistics Working Papers

Investigations of transcript levels on a genomic scale using

hybridization-based arrays led to formidable advances in our

understanding of the biology of many human illnesses. At the same time, these investigations have generated controversy, because of the probabilistic nature of the conclusions, and the surfacing of noticeable discrepancies between the results of studies addressing the same biological question. In this article we present simple and effective data analysis and visualization tools for gauging the degree to which

the finding of one study are reproduced by others, and for integrating multiple studies in a single analysis.

We describe these approaches in …


A Model Based Background Adjustment For Oligonucleotide Expression Arrays, Zhijin Wu, Rafael A. Irizarry, Robert Gentleman, Francisco Martinez Murillo, Forrest Spencer May 2004

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 Feb 2004

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 …


Stochastic Models Based On Molecular Hybridization Theory For Short Oligonucleotide Microarrays, Zhijin Wu, Richard Leblanc, Rafael A. Irizarry Sep 2003

Stochastic Models Based On Molecular Hybridization Theory For Short Oligonucleotide Microarrays, Zhijin Wu, Richard Leblanc, Rafael A. Irizarry

Johns Hopkins University, Dept. of Biostatistics Working Papers

High density oligonucleotide expression arrays are a widely used tool for the measurement of gene expression on a large scale. Affymetrix GeneChip arrays appear to dominate this market. These arrays use short oligonucleotides to probe for genes in an RNA sample. Due to optical noise, non-specific hybridization, probe-specific effects, and measurement error, ad-hoc measures of expression, that summarize probe intensities, can lead to imprecise and inaccurate results. Various researchers have demonstrated that expression measures based on simple statistical models can provide great improvements over the ad-hoc procedure offered by Affymetrix. Recently, physical models based on molecular hybridization theory, have been …