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sv2gsm.py and maf2gsm were updated to be compatible with python 3.12, pandas 2.3.0, and
numpy 2.3.0.
seg2gsm.py re-normalizes the log2(copy ratio) units to be consistent with the DLBclass
published GSM (in this repo at data_tables/gsm/DLBCL.699.163drivers.Sep_23_2022.tsv).
Note:
The CNV log2(CR) normalization is sensitive to the inclusion of X and Y segments in the seg
file. The DLBclass convention is to use only autosome segments. seg2gsm.py also has some
sensitivity to the number of digits for the log2(CR) value in the last column of the input
seg file. The DLBclass convention is to use 3 digits for the log2(CR) value. Seg files
with more digits are also fine, but there can be a small rate of discrepancies (<<1%) with
the published GSM when attempting to reproduce the published CNV GSM. Also of note is that
the total copy ratio data for NCI 414 samples of the DLBclass cohort (published as Schmitz et
al., 2018 NEJM doi: 10.1056/NEJMoa1801445.) was based on SNP arrays while the DFCI 277
sample cohort (Chapuy et al., 2018 Nat. Med doi: 10.1038/s41591-018-0016-8.) was entirely
based on whole exome sequencing data. Going forward we expect that use cases for
DLBclass will be based entirely on sequencing data, WGS or WES.