SBIR-STTR Award

The academic iobio project delivers web-based applications that visualize and provide real-time interactive analysis with multiple different data types generated as part of next-generation sequencing projects. These applications are open-source and provided for free. This proposal aims to develop critical computational infrastructure to enable the iobio project to offer commercial applications, providing more power and functionality than is possible for the academic project. In particular, it is necessary to build multiple components that will facilitate management of large computational resources in an on-demand, scalable and robust manner and provide mechanisms for remote file storage. Additionally, functionality to seamlessly combine real-time analysis which is the mainstay of the academic developments with large scale analysis undertaken by commercial applications will empower all users of sequencing data from clinicians / genetic counsellors to large scale sequencing centres and institutions. The long-term objective of the proposal is to position Frameshift labs to rapidly and easily build new commercially viable web-based applications to tackle current bioinformatics analysis problems. This proposal also includes the development of a commercial application called multibam.iobio that will provide producers and consumers of large scale sequencing studies the means to evaluate the quality of their massive data sets. In order to perform population level genome wide association studies (GWAS) or more focused Mendelian studies on small family pedigrees, the quality of the data must be understood prior to expending large amounts of time and resources on analysis. The multibam.iobio application will visualize high-level statistics allowing outlier samples or data trends to be rapidly identified. More focused real-time analysis will be accessible for all samples. The effectiveness of sequencing projects, from focused somatic variant identification in tumor / normal pairs to population scale GWAS demands consistently high data quality, whether this is the underlying sequence alignments or genetic variants. Multibam.iobio will ensure that all interested parties, regardless of computational experience and resource limitations, can interrogate and fully understand their data.

Public Health Relevance Statement:


Public Health Relevance:
Research into the genetic basis of disease and accurate determination of treatment options is increasingly dependent on DNA sequencing. This project will develop critical infrastructure for the IOBIO project and a web-based, intuitive application that will provide a critical understanding of the quality of sequencing data to everyone involved in analyzing or working with this data. Ensuring the quality of data will help ensure high- quality results from all manner of sequencing based studies and ultimately lead to improved understanding of disease and potential treatment options.

Project Terms:
Back; base; Base Sequence; Big Data; Bioinformatics; Chromosomes; commercial application; Communities; Computer Analysis; Computer Hardware; computer infrastructure; Computer software; Computers; computing resources; Core Facility; cost; Custom; Data; Data Analyses; Data Quality; Data Set; Databases; Development; Disease; DNA; DNA Sequence; DNA Sequencing Facility; Drops; Effectiveness; empowered; Ensure; Equilibrium; experience; Family; Fees; Funding; Galaxy; Generations; Genes; Genetic; genetic counselor; genetic pedigree; genetic variant; Genome; genome wide association study; genomic data; Genomics; Goals; Grant; Human Genome; Imagery; improved; Institution; interest; Internet; Large-Scale Sequencing; Lead; Libraries; Licensing; Metagenomics; Methods; Modeling; next generation sequencing; Online Systems; open source; operation; Performance; Phase; Population; Positioning Attribute; Preparation; public health relevance; Quality Control; Reporting; Research; Research Infrastructure; Resolution; Resources; Sampling; scale up; Sequence Alignment; Software Tools; statistics; task analysis; Techniques; Text; Time; tool; trend; tumor; Variant; web app; whole genome; Work

The precision medicine initiative coupled with advances in genomic research and diagnostics is leading to vast increases in the volume of genomic data being created, with some estimates stating it will outstrip the storage requirements of YouTube by 2025. Ensuring all this data can be cost-effectively managed, and that experts from the biomedical, informatics and medical disciplines can easily collaborate on analysis, and interpretation of results is critical for genomic medicine to realise its potential, both in research, and at the point-of-care. This proposal will develop an easy-to-use, web-based platform to manage and visualize the vast amounts of genomic data already available and projected to be generated. This platform will access data across distributed file systems, and, via a powerful API, connect to customers cloud, or local hardware pipelines and analysis tools. As companies transfer data to the cloud, or use the cloud as an overflow to their internal storage, this data hub will provide uninterrupted data access. Data will be managed in a highly visual environment, providing visual analytics of all available data, and the ability to generate data subsets using search functionality provided by interactive charts and standard text search. Automated data and consistency checks will be performed, and integrated apps built on the IOBIO platform will enable intuitive data analysis, with all results stored, and shareable from within this data hub, promoting close collaboration on projects. Rather than being reduced to static reports, or Excel style spreadsheets, results are stored in the data hub and within these apps. This means that the link between results are supporting data are never severed, so analyses can be repeated, reviewed, or updated based on modified assumptions or data with ease. The objective of this proposal is to develop a commercially viable product to make management of, collaboration on, and understanding of genomic data a reality for medical professionals as well as informatics experts, diagnosticians, and biomedical researchers. Reducing the costs associated with genomic analysis will ensure it can be scaled to support individual focused medicine, and be attractive to a wide customer base. The product is designed for growth, with the addition of analysis modules focused on Mendelian disease genetics and oncology, among others, planned for the future.

Thesaurus Terms:
Address; Base; Bioinformatics; Biomedical Informatics; Clinic; Cohort; Collaborations; Computer Science; Cost; Cost Analysis; Cost Effective; Cost Savings; Coupled; Custom; Data; Data Access; Data Analyses; Data Analytics; Data Hub; Data Management; Data Security; Data Visualization; Design; Diagnosis; Diagnostic; Discipline; Dna Sequencing; Drops; Ensure; Environment; Face; Flexibility; Future; Genetic Diseases; Genome; Genomic Data; Genomic Medicine; Genomics; Growth; Healthcare; Healthcare Systems; Hybrids; Imagery; Improved; Individual; Informatics; Intuition; Link; Location; Medical; Medicine; Member; Mendelian Disorder; Natural Regeneration; Negative Affect; Novel; Oncology; Online Systems; Outcome; Output; Pain; Pathology; Patients; Point Of Care; Precision Medicine Initiative; Productivity; Quality Control; Reporting; Research; Research Personnel; Research Project Grants; Risk; Sampling; Secure; System; Technology; Text; Time; Tool; Update; Uptake; Visual; Web App;