PT  - JOURNAL ARTICLE
AU  - Jun Ding
AU  - Chieh Lin
AU  - Ziv Bar-Joseph
TI  - Cell lineage inference from SNP and scRNA-Seq data
AID  - 10.1101/401943
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 401943
4099  - http://biorxiv.org/content/early/2018/08/30/401943.short
4100  - http://biorxiv.org/content/early/2018/08/30/401943.full
AB  - Several recent studies focus on the inference of developmental and response trajectories from single cell NA-Seq (scRNA-Seq) data. A number of computational methods, often referred to as pseudo-time ordering, have been developed for this task. Recently, CRISPR has also been used to reconstruct lineage trees by inserting random mutations. However, both approaches suffer from drawbacks that limit their use. Here we develop a method to detect significant, cell type specific, sequence mutations from scRNA-Seq data. We show that only a few mutations are enough for reconstructing good branching models. Integrating these mutations with expression data further improves the accuracy of the reconstructed models. As we show, the majority of mutations we identify are likely RNA editing events indicating that such information can be used to distinguish cell types.