Dear community members,
we've prepared a tool for CNV detection (another one) called ClinCNV. It was already used for the analysis of around 5 thousands of samples sequenced on different platforms and the results are quite good, we also performed the benchmarking and found out that the tool is at least not worse than the competitors in germline context and works better for somatic context (using False Discovery Rate and concordance as metrics). You can check out a short presentation of the tool here (around 60 slides).
The tool uses cohorts of samples and read-depth (and BAF for somatic calling). It has quite a lot of features, such as clustering of samples prior to analysis, IGV visualization, polymorphic regions calling, mosaic CNV calling, different options for FDR control, etc. To have a quick overview I'd recommend to go directly to the docs. Try the test run with the command from here.
The limiting factor may be - we used ngs-bits for files preparation, however, it is an easy-to-install package, it is fast and has many useful features.
Please send me any feedback about the tool.
UPD the preprint is here, somatic part of ClinCNV. Please, criticize it. https://www.biorxiv.org/content/10.1101/837971v1
UPD2: ClinCNV's germline CNVs detection procedure and results were not published in any form, and I was not able to upload a preprint to bioRxiv (not due to ethical issues), however I can share a link to my thesis which is citable - pp55-94 describe the analytical performance of the tool for germline CNVs detection. Citation can be done as:
Demidov, German. Methods for detection of germline and somatic copy-number variants in next generation sequencing data. 2019 http://hdl.handle.net/10803/668208
UPD3: Tumor-only calling is implemented. Still requires approx 20 normal samples sequenced with the same enrichment kit. Highly recommended to be used with BAF-files and off-target reads. Limitations: less than 50% of the genome affected by CNVs, purity > 30%, no polyploidies. In summary - fine for blood cancers, maybe not good for 50% of the solid tumors. Still an experimental feature - one may send the results to me if they are unsatisfactory and we can decide what to improve.