Nexus Copy Number is an easy to use yet powerful tool for analyzing and visualizing array CGH data. Nexus provides cross platform copy number analysis on multiple experiments containing multiple samples providing comprehensive gain and loss frequency analysis, statistical confidence values, class comparison analysis, and genomic based clustering.
Nexus Copy Number is truly a unique an innovative product that can improve research productivity by many orders of magnitude compared with other ad hoc software approaches. Just review some of the features below and contact us for a personalized demonstration of the software using your own data
Platform independent
Identify regions of common abberations
Direct support for all commercial arrays
Affymetrix
Agilent
Illumina
Nimblegen
Empire Genomics
ImaGene
GenePix
BlueFuse
Custom file format support
Integrate between different array types.
Nexus Copy Number allows creation of a Frequency plot indicating what percentage of the selected population has a particular Copy Number Aberration (CNA).
The “sort” tool allows the user to sort the samples based on the presence and size of the CNA at a selected location.
Drill down to a single sample
Quickly find genes and regions
Get all available probe level data and complete cytogentic visualization of a single sample with a single mouse click.
Type in a gene symbol or genomic region and have Nexus immediately zoom into the desired region showing samples and any genomic aberrations at that location.
Statistical significance
Visualise copy number profiles between groups
Identify regions of statistical significant CNA at a specified p-value with a single click. Export these regions or drill-down to genes and biological functions with a single mouse click.
Simultaneously view copy number profiles for any groupings of samples (e.g., different tumor types) along with the overall dataset profile. Mouse over any area and see percentage of samples within a call having a specific aberration.
Identify statistically significant regions between groups
Visualise regions of significance differences
Create any pair-wise grouping of samples and perform statistical testing between groups for significant regions. For example, identification of regions with different CNA profiles between young and sick samples as compared to old and healthy cases.
Create specific graphical plots for pair-wise comparisons highlighting areas of significant difference between the groups
Access all annotations with a single click
Perform enrichment analysis
For each region of interest, create an annotation report listing, genes, gene function, gene ontology terms, probe information, and much more with only a single mouse click
Identify Biological processes, molecular functions, and cellular components that could be effected by changes in copy number
Cluster samples based on genomic changes
Cluster samples based on CNA profiles for each sample. Use hierarchical or k-means clustering
