RNA-Seq in the Collaborative Cross
The Collaborative Cross (CC) is a large panel of inbred mouse strains currently being developed for multiple areas of research. Scientists are taking integrated omics-style approaches to collecting data in order to obtain a deeper understanding of the biological mechanisms underlying a number of diverse disease phenotypes. As the cost of the next generation sequencing (NGS) decreases, RNA-sequencing (RNA-seq) has become the favored approach to transcriptomic analyses versus microarrays due to increases in sensitivity and resolution. This is particularly the case with newly defined genomes, where experimental annotation has not caught up to the new microarray platforms. Traditional RNA-seq approaches are not ideal when working with results from collaborative cross studies, as the genomes across individual strains differ considerably. In this chapter we will provide an overview of how to effectively perform RNA-seq analysis from data obtained from the CC mice.
Key wordsAnalysis tools Collaborative Cross RNAseq
Special thanks to James (Matt) Holt, Martin Ferris, Shunping Huang, Seth Greenstein, and Leonard Mcmillan at UNC for support. Thanks to UW Immunology and the Center for Innate Immunity and Immune Diseases for assistance (CIIID).
- 1.Holt J et al (2013) Read annotation pipeline for high-throughput sequencing data. In: Proceedings of the international conference on bioinformatics, computational biology and biomedical informatics, ACM, Washington, DC, USA, p 605–612Google Scholar
- 2.Huang S et al (2013) Transforming genomes using MOD files with applications. In: Proceedings of the international conference on bioinformatics, computational biology and biomedical informatics, ACM, Washington, DC, USA, p 595–604Google Scholar