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Signature Science-led development team offers open source bioinformatics workflows for functional and taxonomic characterization of DNA sequences

Published February 10th, 2020 by Renee

SeqScreen  |  MetScale 

 

Signature Science has collaborated with academic partners to develop open source bioinformatics workflows for the functional and taxonomic characterization of DNA sequences. This has aided in the analysis of complex environmental and clinical samples, detection of virulence elements underlying pathogenesis, assessment of biosecurity risks, prediction of biological functions relevant to the synthetic biology and genome editing industry, characterization of infectious disease outbreaks, and improvement of medical countermeasures through a deeper understanding of host-pathogen interactions. Highlighted below are two examples of these projects.


SeqScreen: Detecting Genes of Interest

gitlab.com/treangenlab/seqscreen

Is this an interesting gene sequence? Great question. Uncovering the taxonomic origin and functional profile of gene sequences is of high interest to biosecurity professionals and fundamental researchers, but it is a challenging and nuanced task to navigate. SeqScreen software was developed in collaboration with Dr. Todd Treangen’s Laboratory at Rice University and other Fun GCAT program team members to leverage multiple open source tools to predict the most probable source organism, the diversity of possible taxonomic lineages, functional gene annotations, and custom biological processes of interest for a given query sequence. We have found SeqScreen to be useful for annotating full-length gene sequences in assembled genomes, as well as gaining the most information possible from short gene fragments in metagenomes, metatranscriptomes, or individual sequences (>50 bp). Please reach out if you have a SeqScreen use case or dataset that you would like our team to evaluate, or a proposal idea that you would like to jointly pursue.

CONTACT: Dr. Krista Ternus, Principal Investigator


MetScale: Analyzing Complex Metagenomes

github.com/signaturescience/metagenomics

Although there are a large number of metagenomics analysis tools available, species-level calls can vary significantly between different taxonomic classifiers. In collaboration with many external partners, the Signature Science team has developed MetScale – a suite of automated workflows to reproducibly run open source metagenomics tools and collectively analyze the results. MetScale enables a more accurate interpretation of results by analyzing taxon assignments that surpass high confidence thresholds across multiple tools, as well as a database query tool that determines if a false positive call was the result of an organism not being present in the reference database. We welcome test datasets and contributions from the open science community to continue to improve this framework.

CONTACT: Dr. Krista Ternus, Principal Investigator


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