Yufeng Wu

ScisTree2 infers cell lineage trees and calls genotypes from single-cell data, achieving higher accuracy and efficiency than existing methods.

This study identifies small peptides encoded by lncRNAs in rice using a multi-omics approach, finding 403 LSEPs across four databases.

EigenDel detects genomic deletions using discordant read-pairs and unsupervised learning, outperforming existing methods in accuracy and sensitivity on low coverage data.

This paper introduces a method to estimate ancestry proportions of an individual's parents and grandparents using genetic data, showing it can distinguish between different ancestry combinations in ancestors.

This paper introduces GTmix, a coalescent-based maximum likelihood method for inferring admixture networks from local gene genealogies, showing improved accuracy with smaller datasets.

This paper introduces circDBG, a method for detecting circular RNA using de Bruijn graphs, showing improved accuracy, efficiency, and sensitivity compared to existing methods.

DeepSV uses a deep convolutional neural network to accurately call long deletions from sequencing data, outperforming existing methods on the 1000 Genomes Project data.

ScisTree infers cell lineage trees from noisy single-cell data using genotype probabilities, achieving high accuracy and efficiency compared to existing methods.

GAPPadder closes gaps in draft genomes more effectively than existing tools by utilizing repeat-associated reads and two-stage local assembly.

CircMarker detects circular RNA using k-mers instead of read mapping, achieving higher accuracy and efficiency than existing tools.