Whole Genome Map Data module

BioNumerics Seven offers a completely new module for the analysis of whole genome maps, i.e. high resolution, ordered whole genome restriction maps from single microbial DNA molecules obtained from the Argus™ Whole Genome Mapping System (www.opgen.com). As whole genome mapping provides highly detailed strain information, it is very well suited for discriminating closely related strains (e.g. outbreaks). The analysis of Whole Genome Map data in BioNumerics Seven is hence mainly focused on strain typing and characterization.

Importing whole genome maps

Straightforward XML-based import of whole genome maps from the Argus™ Whole Genome Mapping System from OpGen® into this new experiment type in BioNumerics Seven. Sample names can be parsed from the file ID.

Comprehensive viewing & search tools

Whole Genome Maps inversionThe various display options allow highlighting genomic differences (indels, duplications). Direct and inverted match indication of fragments allows fast discovery of differences across whole genome maps. Zooming into a specified visible range provides a detailed look at differences at the individual fragment level. Fragments can be annotated with a customizable label for future reference. An intuitive search function picks up whole genome map fragments according to their size, label, etc. Furthermore, a convenient visualization tool is present for a quick, at-a-glance discovery of fragments resulting from a search action.

Accurate map-based clustering

Distinguishing highly related strains is made easy through fast and accurate map-based clustering using in-house developed algorithms, based on size tolerance or pattern based matching of whole genome map fragments, for calculating similarities.

Whole Genome Map clustering

Genomic differences at-a-glance

Pairwise and multiple alignment of whole genome maps, in combination with the highlighting, annotation and alignment options, allow to accentuate genomic differences like inversions or deletions.

Finding discriminating fragments

An exclusive tool for finding discriminating fragments on whole genome maps for a (group of) isolate(s) will make an inventory of such fragments, which can be readily flashed-out by the visualization tool.

Furthermore, comprehensive polymorphism analysis for discriminating between groups of isolates, using the so-called pattern match classes, have the ultimate goal of biomarker screening for a specific group of isolates. Further in depth analysis, such as PCA analysis or matrix mining for instance, is made possible using the powerful and renowned BioNumerics’ analysis tools.

Whole Genome Maps discriminating fragments