RT Journal
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
JF Genome Research 
JO Genome Research 
YR 2016 
FD November 01 
VO 26 
IS 11 
SP 1588 
OP 1599 
DO 10.1101/gr.202903.115 
UL http://genome.cshlp.org/content/26/11/1588.abstract 
AB 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.