Abstract
BackgroundThe analysis of DNA copy number variants (CNV) has increasing impact in the field of genetic diagnostics and research. However, the interpretation of CNV data derived from high resolution array CGH or NGS platforms is complicated by the considerable variability of the human genome. Therefore, tools for multidimensional data analysis and comparison of patient cohorts are needed to assist in the discrimination of clinically relevant CNVs from others.ResultsWe developed GenomeCAT, a standalone Java application for the analysis and integrative visualization of CNVs. GenomeCAT is composed of three modules dedicated to the inspection of single cases, comparative analysis of multidimensional data and group comparisons aiming at the identification of recurrent aberrations in patients sharing the same phenotype, respectively. Its flexible import options ease the comparative analysis of own results derived from microarray or NGS platforms with data from literature or public depositories. Multidimensional data obtained from different experiment types can be merged into a common data matrix to enable common visualization and analysis. All results are stored in the integrated MySQL database, but can also be exported as tab delimited files for further statistical calculations in external programs.ConclusionsGenomeCAT offers a broad spectrum of visualization and analysis tools that assist in the evaluation of CNVs in the context of other experiment data and annotations. The use of GenomeCAT does not require any specialized computer skills. The various R packages implemented for data analysis are fully integrated into GenomeCATs graphical user interface and the installation process is supported by a wizard. The flexibility in terms of data import and export in combination with the ability to create a common data matrix makes the program also well suited as an interface between genomic data from heterogeneous sources and external software tools. Due to the modular architecture the functionality of GenomeCAT can be easily extended by further R packages or customized plug-ins to meet future requirements.
Highlights
The analysis of DNA copy number variants (CNV) has increasing impact in the field of genetic diagnostics and research
Array Comparative genomic hybridization (CGH) is recognized as a first-tier test for DNA copy number variants (CNV) [2] and many laboratories have already established their pipelines for pre-processing of array CGH data
The format is ideal for comparisons of own array CGH data with results from other experiment types or, for example, CNVs that have been reported in literature as a list of genomic intervals
Summary
The analysis of DNA copy number variants (CNV) has increasing impact in the field of genetic diagnostics and research. Tebel et al BMC Bioinformatics (2017) 18:19 Such kind of meta-analysis needs the implementation of additional commercial or free software. A few free software packages offer a comprehensive spectrum of visualization and analysis tools for multidimensional array data operable via a graphical user interface [12,13,14,15,16,17]. What these tools have in common is that they have been designed with the intention to analyze microarray data. As in the case of the IGV, analysis of array data that goes beyond visualization requires the export to the GenePattern software [20], where several web-based features for DNA copy number analysis are provided
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