Simulated exome-sequencing data for a family study of lymphoid cancer

This repository contains all the data files for a simulated exome-sequencing study of 150 families, ascertained to contain at least four members affected with lymphoid cancer.  Please note that previous versions of this repository omitted a key file linking the genotypes of individuals to their family and individual IDs; this file, geno_key.txt, is now included. All other files remain the same as in previous versions.

The simulated data can be found in the files section below. The files are:

1. SLiM_output.txt - contains the SLiM-simulated, exome-wide, SNV data generated under an American-admixture demographic model,  for the American-admixed sub-population only.
2. SLiM_output_chr8&9.txt - contains the SLiM-simulated data above for all source populations as well as the American-admixed sub-population, but only for chromosomes 8 and 9.
3. sample_info.txt - contains pedigree information of all the disease-affected individuals and individuals connecting them along a line of descent, for all 150 ascertained pedigrees.
4. Genotypes.zip -  a zipfile that contains 22 text files of genotypes for each chromosome. The genotypes are for simulated single-nucleotide variants on the exome and are in gene-dosage format. 
5. geno_key.txt – a plain-text file that links the genotyped individuals to their family and individual IDs.
6. SNVmaps.zip -  a zipfile that contains 22 text files giving the single-nucleotide variant information for each chromosome. 
7. familial_cRV.txt - contains the familial causal rare variants for all 150 ascertained pedigrees.
8. study_peds.txt - contains the 150 pedigrees ascertained to contain four or more relatives affected with lymphoid cancer.
9. PLINKfiles.zip -  a zipfile that contains PLINK .fam, .bim and .bed files for all 22 of the chromosomes.

All the scripts used to generate these data can be found in the GitHub repository archived at https://zenodo.org/records/12694914

We have also uploaded one intermediate .Rdata file, Chromwide.Rdata, to save the user substantial time when running the associated RMarkdown script for the simulation. We recommend loading Chromwide.Rdata into your R work-space rather than generating it from scratch.