
SMaSH – a scalable, general marker gene identification framework for single-cell RNA-sequencing
Single-cell RNA-sequencing is revolutionising the study of cellular and tissue-wide heterogeneity in a large number…
Single-cell RNA-sequencing is revolutionising the study of cellular and tissue-wide heterogeneity in a large number…
The recent advances in spatial transcriptomics have brought unprecedented opportunities to understand the cellular heterogeneity…
Organoids enable in vitro modeling of complex developmental processes and disease pathologies. Like most 3D cultures, organoids…
Circular ribonucleic acids (circRNAs) are novel non-coding RNAs that emanate from alternative splicing of precursor…
Single-cell RNA sequencing allows for characterizing the gene expression landscape at the cell type level.…
Single-cell RNA sequencing has led to unprecedented levels of data complexity. Although several computational platforms…
About 15% of human cancer cases are attributed to viral infections. To date, virus expression…
Application of deep learning methods to transcriptomic data has the potential to enhance the accuracy…
Diversity of the T cell receptor (TCR) repertoire is central to adaptive immunity. The TCR…
Detection of somatic mutations using patients sequencing data has many clinical applications, including the identification…