Resource Library

Showing 6 - 10 of 86 results.

ASHG19 Agenda

Full agenda of Broad Institute presentations, posters, exhibit Hall events and more.

PacBio Sequencing

Datasheet for the PacBio Sequencing product

Microbial Genome Sequencing

Datasheet for the Microbial Genome Sequencing product

AGBTPH19 - Application of Lean Manufacturing Methodologies in High Throughput Genomic Sequencing

Peter Trefry1, Sam DeLuca1, Mike Nasuti1, Shannon Adams1, Marissa Gildea1, Doug Gobron1, Tom Howd1, Tim DeSmet1


1Broad Institute of MIT and Harvard, Cambridge, MA


The utility and application of genomics to understand disease, and the continuing trend to utilize genomics in healthcare, results in an ever increasing demand for greater sequence data generation. Despite the significant reductions in per-base sequencing cost over the last decade, the infrastructure, capital, and reagent costs are still relatively expensive. Top of the line sequencers can cost over 1 million dollars per instrument, and sequencing run costs can still be tens of thousands of dollars. With such high fixed cost associated with genome data generation, it is important to maximize capacity utilization and reduce the non-value add and wasteful workflow process steps. We demonstrate the application of lean manufacturing methodologies and visual management techniques to the genomic sequencing workflow, which results in achieving a sequencer utilization rate of around 90%, while three fold scaling our library preparation process to over 300,000 samples destined for exome and whole human genome sequencing annually.


By combining the sample preparation methods for both exome and whole genome sequencing into a unified, modularized workflow, samples and reagent supply chains can be optimized resulting in more efficient, and cost effective processing. Additional benefits include reductions to work in process and overall cycle times. Here, we illustrate the methodologies that enable low cost per base sequence data generation applicable across large sequencing cores, and modest sized data generation groups.

AGBTPH19 - Clinical Validation of Illumina Array-based Genotyping for the All of Us Research Program

Michael DaSilva1, Alyssa Macbeth1, Steven Harrison1, Betty Wolff1, Maegan Harden1, Gina Vicente1, Sarah Babchuck1, Katelyn Flowers1, Kunsang Gyaltsen1, Brian Granger1, George Grant1, Heidi Rehm1, Stacey Gabriel1, Niall Lennon1


1Broad Institute of MIT and Harvard, Cambridge, MA


As the utility of genomics evolves, a need has emerged for large-scale genomic datasets produced in a clinical setting. To satisfy that niche, the Genomics Platform at the Broad Institute has established CAP/CLIA compliant genotyping capabilities at scale. Once such effort requiring these capabilities is the All of Us research project (AoURP). Funded by the National Institutes of Health (NIH), AoURP aims to generate sequencing and genotyping data from 1 million or more research participants across the U.S. Medically actionable results from a pre-defined set of genes (termed the AoU Medically Actionable Panel, AoUMAP) will be returned to participants after orthogonal validation in a clinical validation laboratory. Genotyping will be run using the Illumina All of Us (AoU) array that has been specifically designed with 1.8 million markers across the human genome. AoU array content has been designed to capture pathogenic and likely pathogenic sites (as defined by ClinVar) across the AoUMAP, in addition to pharmacogenetic markers.

As one of three Genome Centers selected by the AoURP program, the Broad Institute Genomics Platform has built the operational and clinical infrastructure required to genotype >300,000 AoURP participants over the next 4-5 years. We performed an analytical validation study to assess the accuracy and precision of the AoU Array. A combination of reference samples, PGx cell lines, and previously tested clinical samples were used to verify that the array is suitable for its intended use as part of the AoURP. In addition, we have established the capacity to meet AoURP scale, while running other concurrent, large-scale projects.

Here we discuss the onboarding process for the new array, the establishment of CLIA/CAP quality standards in our genotyping process, and the results of our analytical validation study.