UPdated GSM processing scripts

1. sv2gsm.py and maf2gsm were updated to be compatible with python 3.12, pandas 2.3.0, and
   numpy 2.3.0.
2. 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.

Added GISTIC files

added GISTIC files
data_tables/additional_gsm_inputs/DLBCL_broad_significance.18Aug2024.tsv
data_tables/additional_gsm_inputs/DLBCL_focal_peaks.18Aug2024.tsv

Initial release V0.1

Scripts to generate figures and tables for DLBclass manuscript