Data Sharing and Collaboration

Interpreting genomic data often depends on previously discovered associations. Researchers need to share data with collaborators in the scientific community to advance the field. As genomic methods become more commonplace, Illumina offers an increasingly wide breadth of flexible and efficient tools for sharing data, accessing public databases, and formatting data for publications.

Faster, automated lab procedures lead to faster and more efficient experiments and more reliable results. And when reliable results are received quickly, research findings can be published sooner.

To enable publication, any informatics solution must be as good at helping scientists get data out of the system as it was at helping scientists get the data in. A LIMS maximizes instrument efficiency; automates critical data capture, quality control, and analysis pipelines; and keeps samples flowing through the lab while tracking associated data and keeping information easily accessible. It should also offer a variety of options for accessing stored data, from ad hoc searches to sophisticated reporting frameworks that can also be used to create custom queries and reports.

A robust API can also help scientists and internal programmers extract data into the format needed for downstream analysis. And once that analysis is complete, scientists can choose any number of ways to summarize and communicate results.