SUMMARY: RNA sequencing data are becoming a major method of choice to study transcriptomes, including the mapping of gene expression quantitative trait loci (eQTLs). RNA sample contamination or swapping is a serious problem for downstream analysis and may result in false discovery and lose power to detect the true biological relationships. When genetic data are available, for example, in eQTL studies or samples have been previously genotyped or DNA sequenced, it is possible to combine genetic data and RNA-seq data to detect sample contamination and resolve sample swapping problems. In this article, we introduce a tool (IDCheck) that allows easy assessment of concordance between genotype (from SNP arrays or DNA sequencing) and gene expression (RNA-seq) samples. IDCheck compares the identity of RNA-seq reads and SNP genotypes using a likelihood-based method. Based on maximum likelihood estimates of relevant parameters, we can detect sample contamination and identify correct sample pairs when swapping occurs. Our tool provides an efficient and convenient way to evaluate and resolve these problems. AVAILABILITY: A complete description of the software is included on the application home page. The software is freely available in the public domain at http://eqtl.rc.fas.harvard.edu/idcheck/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Abstract Summary: We describe an interactive package that provides graphical overviews of the results of whole-genome association studies in datasets with rich multi-dimensional phenotypic information, such as global surveys of gene expression. Windows, Linux and Mac binaries are available from our website. Availability: http://www.sph.umich.edu/csg/weich/software.html Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.

SUMMARY: GENOME proposes a rapid coalescent-based approach to simulate whole genome data. In addition to features of standard coalescent simulators, the program allows for recombination rates to vary along the genome and for flexible population histories. Within small regions, we have evaluated samples simulated by GENOME to verify that GENOME provides the expected LD patterns and frequency spectra. The program can be used to study the sampling properties of any statistic for a whole genome study. AVAILABILITY: The program and C++ source code are available online at http://www.sph.umich.edu/csg/liang/genome/