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Xi'an Jiaotong University Develops TDEseq for Analyzing Gene Expression Dynamics

Xi'an Jiaotong University Develops TDEseq for Analyzing Gene Expression Dynamics

In 2020, Professor Sun Shiquan of Xi'an Jiaotong University endeavored to decipher the genetic foundations of lung adenocarcinoma progression. His investigation revealed a critical gap in existing methodologies: the inability to identify genes with specific temporal expression patterns within single-cell RNA sequencing data.

To address this, Sun's team created TDEseq, an innovative analytical tool designed to pinpoint genes that exhibit dynamic expression changes over time. These genes, pivotal in biological processes, display patterns such as gradual upregulation or intricate temporal fluctuations.

The development of TDEseq faced several challenges. The team explored various fitting functions before adopting shape-constrained I-splines and C-splines, which provided accuracy and robustness against noise. They also addressed the issue of sample heterogeneity by incorporating linear mixed models and scMerge to reduce its effects.

TDEseq's efficiency was further boosted by the introduction of pseudocells, a concept that optimized the processing of large datasets. This innovation ensures TDEseq's utility in analyzing extensive, multi-sample single-cell data, offering a robust tool for comprehending disease progression and developmental dynamics.

The team's subsequent objective is to expand TDEseq's functionalities to spatial transcriptomics, aiming to capture gene expression dynamics across both time and space. This enhancement could offer profound insights into the intricate interactions of genes in health and disease.

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