GoKawiilPPCG cohort, WGS and variant calling
We used data from the PPCG consortium of primary prostate cancer samples from a total of 1,001 prostate cancer donors with 1,172 tumour samples. Informed ethical consent was obtained at clinical follow-up, and was consistent with local research ethics and International Cancer Genome Consortium (ICGC) guidelines (https://icgc.org/). Ethical approval was obtained from local research ethical committees (details are provided in the Supplementary Methods).
Analysis of SVs from genomic data
Simple and complex SV classification method
We conducted SV classification on the PPCG cohort using the cSVc tool18, including also SVs near TARBS and chromothripsis, both abundant in prostate cancer. First, exact breakpoint estimation from our WGS short-read sequencing data was conducted by using split-read information. Specifically, for each sample, we used the median of soft-clipped reads from the corresponding tumour BAM file to obtain corrected breakpoint positions. Next, we used ClusterSV18 to obtain clusters of SVs from the corrected SV data and we also used Battenberg68 to obtain segmented CN files from tumour and normal read coverage files. For each sample, we generated CN files segmented by corrected SV breakpoints by using the corrected SV data, the CN segmentation file, CN coverage and the tumour BAM file. Finally, we conducted simple and complex SV classification (chromothripsis excluded) using the CN-SV segmentation file together with the corrected SV file, ClusterSV file and information about ploidy and purity.
To classify chromothripsis on the PPCG cohort, we used Shatterseek v.0.4, using SV and CN data. We used Shatterseek’s recommended cut-off criteria to obtain high-confidence calls69. Multiple-testing correction was performed on the P values of three statistical tests indicative of chromothripsis (breakpoint enrichment test, exponential clustering test and the fragment joins test) and we used a q-value cut-off of 0.2 for the chromothripsis calls on each chromosome to confine the final high confidence call set.
To obtain the final SV dataset we merged the chromothripsis call set with the remaining simple and complex SV call set. Specifically, we merged calls only if a minimum of 90% of SV call sets spanning the chromothripsis cluster were marked as Complex Unclassified.
Tandem duplication detection
The presence of TDP samples was assessed by using three criteria described previously70. The criteria involve the proportion of tandem duplications, the total tandem duplication count and a TDP score71:
$${\rm{T}}{\rm{D}}{\rm{P}}\,{\rm{s}}{\rm{c}}{\rm{o}}{\rm{r}}{\rm{e}}=-\frac{\sum _{i}|{{\rm{O}}{\rm{b}}{\rm{s}}}_{i}-{{\rm{E}}{\rm{x}}{\rm{p}}}_{i}|}{{\rm{T}}{\rm{D}}}$$
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