Computational Tool Differentiates Between Data From Cancer Cells and Normal Cells – Technology Networks

In an effort to address a major challenge when analyzing large single-cell RNA-sequencing datasets, researchers from The University of Texas MD Anderson Cancer Center have developed a new computational technique to accurately differentiate between data from cancer cells and the variety of normal cells found within tumor samples. The work was published today in Nature Biotechnology.
The new tool, dubbed CopyKAT (copy number karyotyping of aneuploid tumors), allows researchers to more easily examine…

Click here to view the original article.