Biology subjects

Johanson, E.

Publications and source records attributed to Johanson, E..

3 recordsLinked to original sources

bioRxiv2020

precisionFDA Truth Challenge V2: Calling variants from short- and long-reads in difficult-to-map regions

The precisionFDA Truth Challenge V2 aimed to assess the state-of-the-art of variant calling in difficult-to-map regions and the Major Histocompatibility Complex (MHC). Starting with FASTQ files, 20 challenge participants applied their variant calling pipelines and submitted 64 variant callsets for one or more sequencing technologies (~35X Illumina, ~35X PacBio HiFi, and ~50X Oxford Nanopore Technologies). Submissions were evaluated following best practices for benchmarking small variants with the new GIAB benchmark sets and genome stratifications. Challenge submissions included a number of innovative methods for all three technologies, with graph-based and machine-learning methods scoring best for short-read and long-read datasets, respectively. New methods out-performed the 2016 Truth Challenge winners, and new machine-learning approaches combining multiple sequencing technologies performed particularly well. Recent developments in sequencing and variant calling have enabled benchmarking variants in challenging genomic regions, paving the way for the identification of previously unknown clinically relevant variants.

bioinformatics↗

bioRxiv2020

Strengthening the BioCompute Standard by Crowdsourcing on PrecisionFDA

BackgroundThe field of bioinformatics has grown at such a rapid pace that a gap in standardization exists when reporting an analysis. In response, the BioCompute project was created to standardize the type and method of information communicated when describing a bioinformatic analysis. Once the project became established, its goals shifted to broadening awareness and usage of BioCompute, and soliciting feedback from a larger audience. To address these goals, the BioCompute project collaborated with precisionFDA on a crowdsourced challenge that ran from May 2019 to October 2019. This challenge had a beginner track where participants submitted BCOs based on a pipeline of their choosing, and an advanced track where participants submitted applications supporting the creation of a BCO and verification of BCO conformance to specifications. ResultsIn total, there were 28 submissions to the beginner track (including submissions from a bioinformatics masters class at George Washington University) and three submissions to the advanced track. Three top performers were selected from the beginner track, while a single top performer was selected for the advanced track. In the beginner track, top performers differentiated themselves by submitting BCOs that included more than the minimally compliant content. Advanced track submissions were very impressive. They included a complete web application, a command line tool that produced a static result, and a dockerized container that automatically created the BCO as the tool was run. The ability to harmonize the correct function, a simple user experience, and the aesthetics of the tool interface differentiated the tools. ConclusionsDespite being new to the concept, most beginner track scores were high, indicating that most users understood the fundamental concepts of the BCO specification. Novice bioinformatics students were an ideal cohort for this Challenge because of their lack of familiarity with BioCompute, broad diversity of research interests, and motivation to submit high-quality work. This challenge was successful in introducing the BCO to a wider audience, obtaining feedback from that audience, and resulting in a tool novices may use for BCO creation and conformance. In addition, the BCO specification itself was improved based on feedback illustrating the utility of a "wisdom of the crowd" approach to standards development.

bioinformatics↗

bioRxiv2017

Enabling Precision Medicine via standard communication of NGS provenance, analysis, and results

A personalized approach based on a patients or pathogens unique genomic sequence is the foundation of precision medicine. Genomic findings must be robust and reproducible, and experimental data capture should adhere to FAIR guiding principles. Moreover, effective precision medicine requires standardized reporting that extends beyond wet lab procedures to computational methods. The BioCompute framework (https://osf.io/zm97b/) enables standardized reporting of genomic sequence data provenance, including provenance domain, usability domain, execution domain, verification kit, and error domain. This framework facilitates communication and promotes interoperability. Bioinformatics computation instances that employ the BioCompute framework are easily relayed, repeated if needed and compared by scientists, regulators, test developers, and clinicians. Easing the burden of performing the aforementioned tasks greatly extends the range of practical application. Large clinical trials, precision medicine, and regulatory submissions require a set of agreed upon standards that ensures efficient communication and documentation of genomic analyses. The BioCompute paradigm and the resulting BioCompute Objects (BCO) offer that standard, and are freely accessible as a GitHub organization (https://github.com/biocompute-objects) following the \"Open-Stand.org principles for collaborative open standards development\". By communication of high-throughput sequencing studies using a BCO, regulatory agencies (e.g., FDA), diagnostic test developers, researchers, and clinicians can expand collaboration to drive innovation in precision medicine, potentially decreasing the time and cost associated with next generation sequencing workflow exchange, reporting, and regulatory reviews.

scientific communication and education↗