Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved

Income Smoothing, Earnings Quality and Firm Valuation

Abstract:  This study argues that lower variability of earnings does not guarantee income smoothers' higher firm values. Instead, smoothers' earnings should be more value-relevant if they are of high quality, i.e., earnings quality should be considered simultaneously. Sample firms are divided into four groups: quality earnings smoothers, quality earnings non-smoothers, non-quality earnings smoothers, and non-quality earnings non-smoothers. Value relevance of reported earnings is then studied using both the levels and the changes approaches with indicator variables. Results show quality earnings smoothers have the highest price-earnings multiple while non-quality non-smoothers have the lowest price-earnings multiple. Copyright Blackwell Publishers Ltd, 2004.