Systems and methods for tumor clonality analysis

Abstract

Systems and methods of genomic analysis are presented that provide a framework to determine a tumor's clonality, the number and proportion of all major clones, and the variants that distinguish them. Contemplated systems and methods also allow phasing mutations to parental alleles to so time their emergence within the population of tumor cells, and provide an accurate estimate of the amount of contaminating normal tissue that was present in the tumor biopsy.

Description

[0001] This application claims priority to our co-pending US Provisional Application Serial No. 61 / 711467, filed October 9, 2012, which is hereby incorporated by reference in its entirety. technical field [0002] The field of the invention is the computational analysis of genomic data, in particular it relates to the identification of the clonality status of mixed cell populations. Background technique [0003] With the increasing availability of whole genome data and the continuous acceleration of whole genome sequencing, large quantities of data are now available, which requires meaningful analysis to provide information to clinicians or scientists for more effective treatment or drug development. [0004] For example, multiple tumor and matched normal whole genome sequences are now available from projects like The Cancer Genome Atlas (TCGA), where it is difficult to extract relevant information. The problem is further complicated by the need for high coverage (eg, greate...

AI Technical Summary

Problems solved by technology

Most notably, methods known to date fail to allow the identification of tumor progression at the molecular level, giving insight into clonality and potential therapeutic efficacy

From another point of view, the hitherto known methods do not allow identification of clonality and clonal relationships of cell populations in samples containing multiple heterogeneous cells

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