Joint analysis of matched tumor samples with varying tumor contents improves somatic variant calling in the absence of a germline sample Rebecca F. Halperin 1* , Winnie S. Liang 1 , Sidharth Kulkarni 1 , Erica E. Tassone 1 , Jonathan Adkins 1 , Daniel Enriquez 1 , Nhan L. Tran 2 , Nicole C. Hank 3 , James Newell 4 , Chinnappa Kodira 5 , Ronald Korn 3,4 , Michael E. Berens 1 , Seungchan Kim 6 , Sara A. Byron 1 1 Translational Genomics Research Institute, Phoenix AZ 2 Mayo Clinic, Scottsdale AZ 3 Imaging Endpoints, Scottsdale AZ 4 HonorHealth Scottsdale Shea Medical Center, Scottsdale AZ 5 GE Global Research Center, Niskayuna, NY 6 Prairie View A&M University, Prairie View, TX *Correspondence: Dr. Rebecca F. Halperin rhalperin@tgen.org Abstract Archival tumor samples represent a potential rich resource of annotated specimens for translational genomics research. However, standard variant calling approaches require a matched normal sample from the same individual, which is often not available in the retrospective setting, making it difficult to distinguish between true somatic variants and germline variants that are private to the individual. Archival sections often contain adjacent normal tissue, but this normal tissue can include infiltrating tumor cells. Comparative somatic variant callers are designed to exclude variants present in the normal sample, so a novel approach is required to leverage sequencing of adjacent normal tissue for somatic variant calling. Here we present LumosVar 2.0, a software package designed to jointly analyze multiple samples from the same patient. The certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (which was not this version posted July 9, 2018. . https://doi.org/10.1101/364943 doi: bioRxiv preprint