Figure 1: Overview of LongSom.

LongSom’s methodology for detecting somatic SNVs, fusions, and CNAs and subsequently inferring cancer subclones in LR scRNA-seq individual patients data. (1) SNV candidates are detected from pseudo-bulk samples. (2) Population germline SNVs and SNVs present in normal samples (optional) are filtered out. (3) A cell-SNV matrix based on the remaining SNV candidates is computed. (4) A cell-fusion matrix is computed. (5) Using high-confidence cancer fusions and SNVs, cells are reannotated. (6) Following reannotation, SNVs present in non-cancer cells (germlines) are filtered out. (7) cells are clustered based on somatic fusions and SNVs. In parallel, (8) gene expression per cell is computed, (9) CNAs are detected, (10) cells are clustered based on CNAs, and (11) CNA clones are incorporated to the fusions and SNVs clustered matrix.