LTMG: a novel statistical modeling of transcriptional expression states in single-cell RNA-Seq data

• Published in: Nucleic acids research Vol. 47; no. 18; p. e111
• Main Authors: Wan, Changlin, Chang, Wennan, Zhang, Yu, Shah, Fenil, Lu, Xiaoyu, Zang, Yong, Zhang, Anru, Cao, Sha, Fishel, Melissa L, Ma, Qin, Zhang, Chi
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 10.10.2019
• Subjects: Algorithms; Gene Expression Profiling; Gene Expression Regulation - genetics; High-Throughput Nucleotide Sequencing - methods; Methods Online; Models, Statistical; RNA - genetics; Sequence Analysis, RNA - methods; Single-Cell Analysis - methods; Software

Abstract A key challenge in modeling single-cell RNA-seq data is to capture the diversity of gene expression states regulated by different transcriptional regulatory inputs across individual cells, which is further complicated by largely observed zero and low expressions. We developed a left truncat...