TY  - JOUR
A1  - Biezuner, Tamir
A1  - Spiro, Adam
A1  - Raz, Ofir
A1  - Amir, Shiran
A1  - Milo, Lilach
A1  - Adar, Rivka
A1  - Chapal-Ilani, Noa
A1  - Berman, Veronika
A1  - Fried, Yael
A1  - Ainbinder, Elena
A1  - Cohen, Galit
A1  - Barr, Haim M.
A1  - Halaban, Ruth
A1  - Shapiro, Ehud
T1  - A generic, cost-effective, and scalable cell lineage analysis platform
Y1  - 2016/11/01 
JF  - Genome Research 
JO  - Genome Research 
SP  - 1588 
EP  - 1599 
DO  - 10.1101/gr.202903.115 
VL  - 26 
IS  - 11 
UR  - http://genome.cshlp.org/content/26/11/1588.abstract 
N2  - Advances in single-cell genomics enable commensurate improvements in methods for uncovering lineage relations among individual cells. Current sequencing-based methods for cell lineage analysis depend on low-resolution bulk analysis or rely on extensive single-cell sequencing, which is not scalable and could be biased by functional dependencies. Here we show an integrated biochemical-computational platform for generic single-cell lineage analysis that is retrospective, cost-effective, and scalable. It consists of a biochemical-computational pipeline that inputs individual cells, produces targeted single-cell sequencing data, and uses it to generate a lineage tree of the input cells. We validated the platform by applying it to cells sampled from an ex vivo grown tree and analyzed its feasibility landscape by computer simulations. We conclude that the platform may serve as a generic tool for lineage analysis and thus pave the way toward large-scale human cell lineage discovery. 
ER  -