The Roth Lab seeks insight into biological systems through genome- and proteome-scale experimentation and analysis.
Current computational interests:
Systematic analysis of genetic epistasis to identify redundant or compensatory systems and to...
With the emergence of NGS technologies, and sequencing data most of the bioinformaticians mung and wrangle around massive amounts of genomics text. There are several "standardized" file formats (FASTQ, SAM, VCF, etc.) and some tools for manipulating...
github.com - JBrowse is a fast, embeddable genome browser built completely with JavaScript and HTML5, with optional run-once data formatting tools written in Perl.
Headline Features:
Fast, smooth scrolling and zooming. Explore your genome with unparalleled...
github.com - We propose AirLift, a methodology and tool for comprehensively moving mappings and annotations from one genome to another similar genome while maintaining the accuracy of a full mapper.
peerj.com - The sequencing, assembly, and basic analysis of microbial genomes, once a painstaking and expensive undertaking, has become almost trivial for research labs with access to standard molecular biology and computational tools. However, there are a wide...
github.com - odgi provides an efficient and succinct dynamic DNA sequence graph model, as well as a host of algorithms that allow the use of such graphs in bioinformatic analyses.
Careful encoding of graph entities allows odgi to efficiently...
www.genomicus.bio.ens.psl.eu - Genomicus is a genome browser that enables users to navigate in genomes in several dimensions: linearly along chromosome axes, transversaly across different species, and chronologicaly along evolutionary time.
Once a query gene has been entered, it...
cloud.google.com - Explore genetic variation interactively. Compare entire cohorts in seconds with SQL-like queries. Compute transition/transversion ratios, genome-wide association, allelic frequency and more.
Process big genomic data easily. Run batch analyses...
shendurelab.github.io - LACHESIS is method that exploits contact probability map data (e.g. from Hi-C) for chromosome-scale de novo genome assembly.
Further information about LACHESIS, including source code, documentation and a user's guide are available...