Novel computational tool enhances single-cell sequencing to uncover genetic variants
Single-nucleotide variants (SNVs) are changes at specific positions in a DNA sequence that can help classify and explain differences in disease susceptibility across populations. While single-cell sequencing provides valuable insights into cellular differences within diverse tissue samples, current tools can only detect a small number of SNVs, limiting information on genetic ancestry. To help bridge this gap, researchers led by Ken Chen, Ph.D., developed a more sensitive computational tool called Monopogen that accurately detects SNVs from...