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Adaptive nanopore sequencing for single cell characterization of cancer mutations and gene rearrangements

Grimes, S. M.; Kim, H. S.; Roy, S.; Sathe, A.; Ayala, C. I.; Almeida-Notestine, A. F.; Haebe, S.; Shree, T.; Levy, R.; Lau, B. T.; Ji, H. P.

2022-11-24 genomics
10.1101/2022.11.22.517284 bioRxiv
Show abstract

In this proof-of-concept study, we developed a single cell method that identifies somatic alterations found in coding regions of mRNAs and integrates these mutation genotypes with their matching cell transcriptomes. We used nanopore adaptive sampling on single cell cDNA libraries, generated long read sequences from target gene transcripts and identified coding variants among individual cells. Short-read single cell transcriptomes characterized the cell types with mutations. We delineated CRISPR edits from a cancer cell line. From primary cancer samples, we targeted hundreds of cancer genes, identified somatic coding mutations and a gene rearrangement among individual tumor cells.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.