QUANTIFYING UNCERTAINTY IN GENOTYPE CALLS

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 at these calls. Various sophisticated statistical procedures have been proposed for transforming raw data into genotype calls. We find that variability in microarray output quality across different SNPs, different arrays, and different sample batches has substantial inuence on the accuracy of genotype calls made by existing algorithms. Failure to account for these sources of variability, GWAS run the risk of adversely affecting the quality of reported findings. In this paper we present solutions based on a multi-level mixed model. Software implementation of the method described in this paper is available as free and open source code in the crlmm R/BioConductor.

EXPLORATION, NORMALIZATION, AND GENOTYPE CALLS OF HIGH DENSITY OLIGONUCLEOTIDE SNP ARRAY DATA

In most microarray technologies, a number of critical steps are required to convert raw intensity measurements into the data relied upon by data analysts, biologists and clinicians. These data manipulations, referred to as preprocessing, can influence the quality of the ultimate measurements. In the last few years, the high-throughput measurement of gene expression is the most popular application of microarray technology. For this application, various groups have 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 the technology. Currently, other applications of microarrays are becoming more and more popular. In this paper we describe a preprocessing methodology for a technology designed for the identification of DNA sequence variants in specific genes or regions of the human genome that are associated with phenotypes of interest such as disease. In particular we describe methodology useful for preprocessing Affymetrix SNP chips and obtaining genotype calls with the preprocessed data. We demonstrate how our procedure improves existing approaches using data from three relatively large studies including one in which large number independent calls are available. Software implementing these ideas are avialble from the Bioconductor oligo package.

A large-capacity memory system that recognizes the calls and songs of individual birds.

Auditory responses in the caudomedial neostriatum (NCM) of the zebra finch (Taeniopygia guttata) forebrain habituate to repeated presentations of a novel conspecific song. This habituation is long lasting and specific to individual stimuli. We here test the acoustic and ethological basis of this stimulus-specific habituation by recording extracellular multiunit activity in the NCM of awake male and female zebra finches presented with a variety of conspecific and heterospecific vocalizations, white noise, and tones. Initial responses to conspecific song and calls and to human speech were higher than responses to the other stimuli. Immediate habituation rates were high for all novel stimuli except tones, which habituated at a lower rate. Habituation to conspecific calls and songs outlasted habituation to other stimuli. The extent of immediate habituation induced by a particular novel song was not diminished when other conspecific songs were presented in alternation. In addition, the persistence of habituation was not diminished by exposure to other songs before testing, nor was it influenced by gender or laterality. Our results suggest that the NCM is specialized for remembering the calls and songs of many individual conspecifics.