CNVinspector for the Evaluation of Copy Number Variations
CNVinspector for the Evaluation of Copy Number Variations
CNVinspector is dedicated for the assessment and comparison of CNVs between single patients or groups of 'cases' against 'controls'. The programme is entirely web-based without the need for local software installation. Users can upload CNVs into our database as tab-delimited or space-delimited tables either with genome build 36 or 37 coordinates. Hence, tables containing the columns 'Chromosome', 'CNV start-position', 'CNV end-position', 'Deletion'(1/0), and 'Duplication'(0/1) can be uploaded from one's own computer as a file, or directly pasted into an input field (eg, from a spread sheet or word processor application). Data privacy is guaranteed by the database, which restricts data access to the owners. Users can, however, make their projects public at any time or share them only with selected cooperation partners.
After data upload, CNVinspector offers two strategies to inspect and analyse the data. (1) The 'simple search' module is optimised for quick inspection and analysis of single patients. It provides default settings, which automatically choose the reference dataset depending on genome build and platform (figure 1). (2) In the 'advanced search' module, CNV data from entire studies can be analysed and filtered in-depth. Patient data can be compared with a set of own control data, or data from the DGV database, by setting thresholds either for the frequency or the absolute number of a CNV in cases versus controls. Then only those duplications or deletions are considered that occur with a minimum frequency (or count) in the cases group and below a maximum frequency in the controls group. This allows quick discovery of CNVs that are enriched in the 'cases' group and to filter out 'common' CNVs. The programme also features the application of positive controls, for example, to find CNVs that are shared between individuals or cohorts with similar phenotype(s).
(Enlarge Image)
Figure 1.
On the 'display/find CNV' page, the user can choose 'case' and 'control' data by scrolling through the table, which can be sorted by clicking on the table heads. Control data can be chosen according to technology and sample numbers. On the left side, researchers can define their filter criteria, or may chose to inspect specific chromosomal positions. If the user wants to depict the clinical CNVs along with phenotypes from the DECIPHER database, she has to be logged in and to check the respective field (top left). Access the article online to view this figure in colour.
The comparison is usually completed within a few seconds. The remaining CNVs are then listed together with the genes affected by the CNVs. Beside the comparison of CNVs against controls, CNVinspector also allows the inspection of single CNVs and their genomic contents. Here, all CNVs in the cases and control group(s) are plotted on a virtual chromosome; duplications are colour-coded in blue and deletions in red. Hyperlinks to the GeneDistiller candidate search engine are provided for the entire region and for the single genes therein (figure 2). This enables the user to prioritise these genes and to look for known disorders, interaction partners and potential functional networks. CNVinspector also provides the possibility to compare own data with data from the DECIPHER database. Hence, additional clinical and disease-relevant annotations can be found.
(Enlarge Image)
Figure 2.
Graphic output showing the position, expansion, frequency and reference for each CNV. The chromosomal positions are given at the top. The green bars depict the genes, which are affected by the CNV. Deletions are coloured in red, duplications in blue. The CNVs contained in the reference sample(s) are grouped separately below. At the bottom, cases from the DECIPHER database are plotted along with their phenotype description (if available). All data is also presented as a table below the plot with hyperlinks to NCBI, ENSEMBL, and GeneDistiller for more detailed gene information. Access the article online to view this figure in colour.
We suggest storing the results in the HTML format with all the hyperlinks preserved. The ensuing filename contains the chromosome number and the genetic positions of the CNV. This way, the user can resume her work at any time and inspect interesting genes via the hyperlinks.
Since the datasets in the DGV database were generated on different platforms, users are advised to restrict their comparisons mainly to data that were obtained with a similar technology. This greatly reduces the risk of method-specific artefacts.
Input and Output
CNVinspector is dedicated for the assessment and comparison of CNVs between single patients or groups of 'cases' against 'controls'. The programme is entirely web-based without the need for local software installation. Users can upload CNVs into our database as tab-delimited or space-delimited tables either with genome build 36 or 37 coordinates. Hence, tables containing the columns 'Chromosome', 'CNV start-position', 'CNV end-position', 'Deletion'(1/0), and 'Duplication'(0/1) can be uploaded from one's own computer as a file, or directly pasted into an input field (eg, from a spread sheet or word processor application). Data privacy is guaranteed by the database, which restricts data access to the owners. Users can, however, make their projects public at any time or share them only with selected cooperation partners.
After data upload, CNVinspector offers two strategies to inspect and analyse the data. (1) The 'simple search' module is optimised for quick inspection and analysis of single patients. It provides default settings, which automatically choose the reference dataset depending on genome build and platform (figure 1). (2) In the 'advanced search' module, CNV data from entire studies can be analysed and filtered in-depth. Patient data can be compared with a set of own control data, or data from the DGV database, by setting thresholds either for the frequency or the absolute number of a CNV in cases versus controls. Then only those duplications or deletions are considered that occur with a minimum frequency (or count) in the cases group and below a maximum frequency in the controls group. This allows quick discovery of CNVs that are enriched in the 'cases' group and to filter out 'common' CNVs. The programme also features the application of positive controls, for example, to find CNVs that are shared between individuals or cohorts with similar phenotype(s).
(Enlarge Image)
Figure 1.
On the 'display/find CNV' page, the user can choose 'case' and 'control' data by scrolling through the table, which can be sorted by clicking on the table heads. Control data can be chosen according to technology and sample numbers. On the left side, researchers can define their filter criteria, or may chose to inspect specific chromosomal positions. If the user wants to depict the clinical CNVs along with phenotypes from the DECIPHER database, she has to be logged in and to check the respective field (top left). Access the article online to view this figure in colour.
The comparison is usually completed within a few seconds. The remaining CNVs are then listed together with the genes affected by the CNVs. Beside the comparison of CNVs against controls, CNVinspector also allows the inspection of single CNVs and their genomic contents. Here, all CNVs in the cases and control group(s) are plotted on a virtual chromosome; duplications are colour-coded in blue and deletions in red. Hyperlinks to the GeneDistiller candidate search engine are provided for the entire region and for the single genes therein (figure 2). This enables the user to prioritise these genes and to look for known disorders, interaction partners and potential functional networks. CNVinspector also provides the possibility to compare own data with data from the DECIPHER database. Hence, additional clinical and disease-relevant annotations can be found.
(Enlarge Image)
Figure 2.
Graphic output showing the position, expansion, frequency and reference for each CNV. The chromosomal positions are given at the top. The green bars depict the genes, which are affected by the CNV. Deletions are coloured in red, duplications in blue. The CNVs contained in the reference sample(s) are grouped separately below. At the bottom, cases from the DECIPHER database are plotted along with their phenotype description (if available). All data is also presented as a table below the plot with hyperlinks to NCBI, ENSEMBL, and GeneDistiller for more detailed gene information. Access the article online to view this figure in colour.
We suggest storing the results in the HTML format with all the hyperlinks preserved. The ensuing filename contains the chromosome number and the genetic positions of the CNV. This way, the user can resume her work at any time and inspect interesting genes via the hyperlinks.
Since the datasets in the DGV database were generated on different platforms, users are advised to restrict their comparisons mainly to data that were obtained with a similar technology. This greatly reduces the risk of method-specific artefacts.
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