Physical Sciences and Mathematics Commons^™

Cloudaligner: A Fast And Full-Featured Mapreduce Based Tool For Sequence Mapping, Tung Nguyen, Weisong Shi, Douglas Ruden

Wayne State University Associated BioMed Central Scholarship

Abstract

Background

Research in genetics has developed rapidly recently due to the aid of next generation sequencing (NGS). However, massively-parallel NGS produces enormous amounts of data, which leads to storage, compatibility, scalability, and performance issues. The Cloud Computing and MapReduce framework, which utilizes hundreds or thousands of shared computers to map sequencing reads quickly and efficiently to reference genome sequences, appears to be a very promising solution for these issues. Consequently, it has been adopted by many organizations recently, and the initial results are very promising. However, since these are only initial steps toward this trend, the developed software does …

A Supermatrix Analysis Of Genomic, Morphological, And Paleontological Data From Crown Cetacea, Jonathan H. Geisler, Michael R. Mcgowen, Guang Yang, John Gatesy

Wayne State University Associated BioMed Central Scholarship

Abstract

Background

Cetacea (dolphins, porpoises, and whales) is a clade of aquatic species that includes the most massive, deepest diving, and largest brained mammals. Understanding the temporal pattern of diversification in the group as well as the evolution of cetacean anatomy and behavior requires a robust and well-resolved phylogenetic hypothesis. Although a large body of molecular data has accumulated over the past 20 years, DNA sequences of cetaceans have not been directly integrated with the rich, cetacean fossil record to reconcile discrepancies among molecular and morphological characters.

Results

We combined new nuclear DNA sequences, including segments of six genes (~2800 …

Bio::Phylo-Phyloinformatic Analysis Using Perl, Rutger A. Vos, Jason Caravas, Klaas Hartmann, Mark A. Jensen, Chase Miller

Wayne State University Associated BioMed Central Scholarship

Abstract

Background

Phyloinformatic analyses involve large amounts of data and metadata of complex structure. Collecting, processing, analyzing, visualizing and summarizing these data and metadata should be done in steps that can be automated and reproduced. This requires flexible, modular toolkits that can represent, manipulate and persist phylogenetic data and metadata as objects with programmable interfaces.

Results

This paper presents Bio::Phylo, a Perl5 toolkit for phyloinformatic analysis. It implements classes and methods that are compatible with the well-known BioPerl toolkit, but is independent from it (making it easy to install) and features a richer API and a data model that is …