The Society of Nuclear Medicine and Molecular Imaging (SNMMI) and 10 other professional societies have issued new appropriate use criteria (AUC) for lymphoscintigraphy in sentinel node mapping and lymphedema/lipedema. The criteria, summarized in the April issue of The Journal of Nuclear Medicine (JNM), include a list of relevant clinical scenarios, a systematic review of evidence in the literature, and a systematic analysis of available evidence, followed by grading each of the clinical scenarios.
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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
Washington [US], January 19 (ANI): 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.
Credit: MD Anderson Cancer Center
HOUSTON 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 the complex data obtained from large single-cell RNA-sequencing experiments, which deliver gene expression data from many thousands of individual cells.
CopyKAT uses that gene expression data to look for aneuploidy, or the presence of abnormal chromosome numbers, which is common in most cancers, said study senior author Nicholas Navin, Ph.D., associate professor of Genetics and Bioinformatics & Computational Biology. The tool also helps to i