Interactive summary of the individual bins with abnormal coverage as detected by 'call.abnomal.cov'.
the data.frame with the results.
the height of the plot in the webpage. Default is "500px".
A number of simple metrics are displayed, to get an idea of the quality of the calls. For normal samples we would expect: the amount of called genome in each sample to be somewhat similar; the copy number estimates to locate near integer values; No systematic calls (i.e. called in all samples). The different tabs of the application display related metrics. The use can interactively tweak a number of filtering parameter to get a subset of high-quality calls. These filtering parameters are
False Discovery Ratesignificance threshold, reduce it to get higher confidence calls.
Deviation from the CN 2how different a call should be compared to the estimated *C*opy *N*umber 2. Force a minimum deviation if you see calls too close to CN 2 (second tab).
Maximum of single bins (Kb)automatically chooses a significance threshold that gives the specified maximum of genome affected by single-bin calls. Useful to force higher stringency for outlier samples (but keep them).
Minimum read coverage in referencemappability threshold. Increase this number to remove calls in regions with low coverage in the reference samples.
a shiny app in the web browser. When the 'Export' button is pressed, the resulting data.frame is returned.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.