2014/02/20 by Vinod Kumar Yadav, Subhajyoti De · 1 citation
Biochemistry, Genetics and Molecular Biology · Medicine · #Cancer Genomics and Diagnostics #Single-cell and spatial transcriptomics #Pancreatic and Hepatic Oncology Research
paper · pdf · doi:10.1093/bib/bbu002
openalex publication_date 2014/02/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
Solid tumor samples typically contain multiple distinct clonal populations of cancer cells, and also stromal and immune cell contamination. A majority of the cancer genomics and transcriptomics studies do not explicitly consider genetic heterogeneity and impurity, and draw inferences based on mixed populations of cells. Deconvolution of genomic data from heterogeneous samples provides a powerful tool to address this limitation. We discuss several computational tools, which enable deconvolution of genomic and transcriptomic data from heterogeneous samples. We also performed a systematic comparative assessment of these tools. If properly used, these tools have potentials to complement single-cell genomics and immunoFISH analyses, and provide novel insights into tumor heterogeneity.