The Globus Genomics solution addresses the challenges that researchers face when dealing with NGS analysis on a large scale. It combines state-of-the-art algorithms with sophisticated data management tools, a powerful graphical workflow environment, and a cloud-based elastic computational infrastructure. Globus Genomics is software-as-a-service, delivered as a monthly subscription with the appropriate level of resources to meet your specific needs.
Nancy Cox's laboratory focuses on the identification and characterization of genetic variation influencing susceptibility to complex disorders, those influenced by more than one factor. Dr. Cox and her research team envisioned developing an exome analysis pipeline that utilizes multiple variant calling algorithms and a consensus calling approach. The goal was to implement a user-friendly variant calling pipeline that would yield high quality data in a timely and computationally efficient manner. Prior to the development of this pipeline, the group struggled with slow transfer of data and sub quality variant calls from single calling algorithms, making subsequent analysis quite difficult. In addition, most available variant calling algorithms have a steep learning curve, which prohibited rotating students and students with primarily biological background from being able to successfully conduct exome analyses, even on small data sets.
To address these issues, the Cox Lab collaborated with the Globus Genomics team to create a Globus Genomics / Galaxy-based multi-caller consensus exome pipeline, providing both high quality results and ease of use. The lab also leveraged Globus Online data transfer service (built into Globus Genomics), which significantly reduced the time spent moving data. Through the incorporation of three variant calling algorithms as well as the development of a consensus-calling program, we have vastly improved the quality of the end result variants from exome sequencing.
To date, it is clear from local and national responses to the pipeline, that the development of this analysis platform is a much-needed step in the right direction for working with large scale sequencing data.
Women of the African Diaspora experience a disproportionate burden of aggressive, early-onset breast cancer that lacks expression of the estrogen receptor (ER), progesterone receptor (PR) and HER-2/neu. This is in comparison to all other races for reasons that remain unknown and, importantly, understudied. The higher frequency of early-onset and aggressive breast cancer in women of African ancestry is at least in part due to differences in the distribution of genetic risk factors. The advent of massively parallel sequencing often referred to as next-generation sequencing (NGS), has brought an unprecedented opportunity to screen multiple genes simultaneously.
BROCA, a cancer risk panel which captures genomic regions including BRCA1, BRCA2, TP53, ATM, BARD1, CHEK2, PALB2, PTEN, CDH1 etc., was developed for the evaluation of patients with a suspected hereditary cancer predisposition. As the most effective strategy to examine the contribution of an inherited predisposition to breast cancer is the systematic screening for pathogenic variants in breast cancer cases as compared to controls, the Olopade Lab aims to conduct BROCA sequencing on 1,000 breast cancer patients and 1,000 controls ascertained in Ibadan, Southwest, Nigeria. This will allow us to estimate the true burden of disease caused by inherited mutations in a large cohort of women of African ancestry. We have worked on building variant calling and filtration system on Globus Genomics (globus.org/genomics), which allows biomedical researchers to quickly analyze large NGS datasets in a fully automated manner, once desirable analytic tools are appropriately installed. Currently, we employ GATK v.2.8 Haplotype Caller and Unified Genotyper, Atlas2, as well as FreeBayes to analyze both single nucleotide variants (SNVs) and insertions and deletions (Indels). SNVs and Indels called with high concordance among four models can be filtered by a Consensus Genotyper which combines the output of multiple variant calling algorithms to improve performance of the classifier. Variants identified can be annotated using multiple libraries on ANNOVAR for further analyses. To date, we have successfully sequenced 400 cases and 400 controls and the variants are being processed on the pipeline. We present the mutation spectrum and other findings at the ASHG 2014 conference.
Globus Genomics has been extremely effective for our exome analysis pipelines. The platform is easy to use, and running in a cloud-based environment has relieved our dependence on local server availability and storage space, which is especially important as our analysis needs continue to grow.
Dr. William B. Dobyns, M.D. Professor - Center for Integrative Brain Research
Seattle Children's Research Institute, University of Washington
We needed a solution that would give us flexibility to extend our analysis pipelines and apply them to very large data sets. Globus Genomics has provided us with a key set of tools and scalable infrastructure to support our research needs.
Dr. Nancy J. Cox, Ph.D. Professor, Section Chief - Genetic Medicine
Department of Medicine, University of Chicago
Globus Genomics is a very powerful platform and the integrated data movement capability has become one of our favorite tools for Next Generation data analysis, allowing us to transfer large data sets easily and efficiently.
Dr. Ghayda Mirzaa, M.D. Center for Integrative Brain Research
Seattle Children's Research Institute
Globus Genomics is very collaborative and user-friendly. It's great for a lab that's on a budget and has minimal people. It's been good for us.
Mark Sasaki Postdoctoral Researcher in the Onel lab
Familial Cancer Clinic at University of Chicago Medicine