Annotation for CNV (copy number variation)
WGAViewer has some limited functions to display and annotate copy number variations. It takes the input of the flat text 'rawcnv' file, as outputted from the PennCNV software (Wang et al. 2007), or from other sources in such a format.
You need to visit the PennCNV website for more detailed description of the 'rawcnv' format. We do provide one exemple dataset for demonstrating the annotation function of the WGAViewer software. This paper described the results included in this example. The following instructions are based on this example.
(c1) Load 'rawcnv' file
To load the 'rawcnv' data file, click on menu “File->Copy number variation -> Load PennCNV output 'rawcnv'” (Figure c-1). You may load multiple files at a time. Different files will be plotted in different colors.
Figure c-1 Load 'rawcnv' data file (Click to enlarge)
Click on the 'ok' button, the WGAViewer program will output a short summary onto the 'log' panel, and will then start the annotation:
(c2) Annotation for CNV coordinates
Instead of directly using the coordinates included in the 'rawcnv' file, WGAViewer would like to connect to the latest genome build to search for the most updated genome coordinates. Sometimes the differences between genome builds will significantly change the relationships between CNV and genes, and keeping the annotation with the most updated genome build will minimize the potential mistakes in interpreting the results. This procedure may take several minutes, depending on the number of CNVs included in the data file. After the annotation, a file named '.[your rawcnv file].snp' will be saved in the same folder of the 'rawcnv' data file. The next time when you load the same rawcnv file, this annotation will be skipped, and the coordinates stored in the '.snp' file will be directly used. However, if you need to re-run this annotation, simple delete the '.snp' file in the data folder.
(c3) Genome overview
Figure c-3 shows the immediate output of the CNV coordinate annotation procedure (c2). In this example, the patient data file (the data file with an odd number) is plotted in red background, and the control data file (the data file with an even number) is plotted in green background. And a deletion will always be plotted in red, while a duplication will always be plotted in blue. The image sizes of the chromosomes and CNVs in this plot are scaled in accordance with their actual sizes. To view the detailed information on certain chromosomes, simply click on the chromosome images. In this example (Figure c-3), we clicked on chromosome 16.
Figure c-3 Genome overview of CNVs (Click to enlarge)
(c4) Chromosome navigation
Figure c-4 Chromosome view (Click to enlarge)
Figure c-4 shows the CNVs plotted along chromosome 16. Again, the patient data file (the data file with an odd number) is plotted in red background, and the control data file (the data file with an even number) is plotted in green background. And a deletion will always be plotted in red, while a duplication will always be plotted in blue. We observed a very large deletion at the location of around 17Mb in schizophrenia patients (Figure c-4, red arrow). We then move mouse onto the coordinate ruler (green rectangle above the red arrow) to zoom into the genomic region (Figure c-5).
Figure c-5 Chromosome navigation (Click to enlarge)
Using the navigation/zooming tools (Figure c-5, red oval) with the coordinate ruler, we focus onto the large deletion on chromosome 16, from 15.0Mb to 16.2Mb. And then we press the "Annotate" button (Figure c-5, red arrow).
Figure c-5 Annotation for CNV (Click to enlarge)
Figure c-5 shows the annotation results. In this figure. we see that this large deletion (Figure c-5, green arrow) on chromosome 16p13.11-p12.4, size of 2.69 Mb, fully deletes region including the gene NDE1 (Figure c-5, red arrow) , which is an important schizophrenia candidate gene, and binds to DISC1 in brain developmental processes.
These results have been published in our recent paper:
Need AC*, Ge D*, Weale ME*, Maia J, Feng S, Heinzen EL, Shianna KV, Yoon W, Kasperavičiūtė D, Gennarelli M, Strittmatter WJ, Bonvicini C, Rossi G, Jayathilake K, Cola PA, McEvoy JP, Keefe RSE, Fisher EMC, St. Jean PL, Giegling I, Hartmann AM, Möller H, Ruppert A, Fraser G, Crombie C, Middleton LT, St. Clair D, Roses AD, Muglia P, Francks C, Rujescu D, Meltzer HY, Goldstein DB. A Genome-Wide Investigation of SNPs and CNVs in Schizophrenia. PLoS Genet 2009 Feb; 5 (2) : e1000373. doi:10.1371/journal.pgen.1000373