Biology subjects

Doreen Ware

Publications and source records attributed to Doreen Ware.

4 recordsLinked to original sources

bioRxiv2015

Architecting a distributed bioinformatics platform with iRODS and iPlant Agave API

Over the past few years, cloud-based platforms have been proposed to address storage, management, and computation of large-scale data, especially in the field of genomics. However, for collaboration efforts involving multiple institutes, data transfer and management, interoperability and standardization among different platforms have imposed new challenges. This paper proposes a distributed bioinformatics platform that can leverage local clusters with remote computational clusters for genomic analysis using the unified bioinformatics workflow. The platform is built with a data server configured with iRODS, a computation cluster authenticated with iPlant Agave system, and web server to interact with the platform. A Genome-Wide Association Study workflow is integrated to validate the feasibility of the proposed approach.

Bioinformatics↗

bioRxiv2015

Construction of the third generation Zea mays haplotype map

BackgroundCharacterization of genetic variations in maize has been challenging, mainly due to deterioration of collinearity between individual genomes in the species. An international consortium of maize research groups combined resources to develop the maize haplotype version 3 (HapMap 3), built from whole genome sequencing data from 1,218 maize lines, covering pre-domestication and domesticated Zea mays varieties across the world.\n\nResultsA new computational pipeline was set up to process over 12 trillion bp of sequencing data, and a set of population genetics filters were applied to identify over 83 million variant sites.\n\nConclusionsWe identified polymorphisms in regions where collinearity is largely preserved in the maize species. However, the fact that the B73 genome used as the reference only represents a fraction of all haplotypes is still an important limiting factor.

Bioinformatics↗

bioRxiv2014

New whole genome de novo assemblies of three divergent strains of rice (O. sativa) documents novel gene space of aus and indica

The use of high throughput genome-sequencing technologies has uncovered a large extent of structural variation in eukaryotic genomes that makes important contributions to genomic diversity and phenotypic variation. Currently, when the genomes of different strains of a given organism are compared, whole genome resequencing data are aligned to an established reference sequence. However when the reference differs in significant structural ways from the individuals under study, the analysis is often incomplete or inaccurate. Here, we use rice as a model to explore the extent of structural variation among strains adapted to different ecologies and geographies, and show that this variation can be significant, often matching or exceeding the variation present in closely related human populations or other mammals. We demonstrate how improvements in sequencing and assembly technology allow rapid and inexpensive de novo assembly of next generation sequence data into high-quality assemblies that can be directly compared to provide an unbiased assessment. Using this approach, we are able to accurately assess the \"pan-genome\" of three divergent rice varieties and document several megabases of each genome absent in the other two. Many of the genome-specific loci are annotated to contain genes, reflecting the potential for new biological properties that would be missed by standard resequencing approaches. We further provide a detailed analysis of several loci associated with agriculturally important traits, illustrating the utility of our approach for biological discovery. All of the data and software are openly available to support further breeding and functional studies of rice and other species.

Genomics↗

bioRxiv2014

A GWAS platform built on iPlant cyber-infrastructure

We demonstrated a flexible Genome-Wide Association Study (GWAS) platform built upon the iPlant Collaborative Cyber-infrastructure. The platform supports big data management, sharing, and large scale study of both genotype and phenotype data on clusters. End users can add their own analysis tools, and create customized analysis workflows through the graphical user interfaces in both iPlant Discovery Environment and BioExtract server.

Bioinformatics↗