Gillian Chu

LAML-Pro jointly infers cell genotypes and lineage trees from lineage tracing data, improving accuracy by correcting genotype errors and producing more spatially coherent trees.

This paper introduces LAML, a method for inferring time-scaled cell lineage trees from CRISPR-based lineage tracing data, showing improved accuracy over existing methods.

The paper improves the scalability of phylogenetic placement by combining SCAMPP with FastTree, achieving scalability comparable to APPLES-2 and better accuracy than other methods.

CNAViz improves copy-number segmentation in DNA sequencing data by combining local and global approaches, achieving better accuracy than existing methods in simulated and real data.

UPP2 improves alignment accuracy for large datasets with sequence length heterogeneity by reducing runtime while maintaining accuracy comparable to UPP.