Qiang Su

ARCADE improves spatial transcriptomic analysis by separating cell abundance from transcriptional state, enhancing deconvolution accuracy and interpretability in complex tissues.

This paper introduces a method to improve RNA-seq transcript quantification by reducing mapping ambiguity through minimal-shared region analysis, showing improved accuracy in isoform detection and abundance estimation.

GaussF improves isoform quantification by using a theoretical Gaussian model to correct sequencing biases without empirical data, outperforming existing tools.

This paper benchmarks scRNA-seq pipelines using two metrics to assess biological fidelity across simulated and real datasets, finding STARsolo performs best in preserving cell identities and marker expression.

CLT-seq provides a simple, unbiased method for poly(A)-tail profiling, revealing dynamic ncRNA regulation similar to mRNA.