Publications – Center for Communicable Disease Dynamics

Single-cell eQTL models reveal dynamic T cell state dependence of disease loci.

Author(s): Nathan A, Asgari S, Ishigaki K, Valencia C, Amariuta T, Luo Y, Beynor JI, Baglaenko Y, Suliman S, Price AL, Lecca L, Murray MB, Moody DB, Raychaudhuri SJournal: NaturePMID: 35545678 May 2022

Non-coding genetic variants may cause disease by modulating gene expression. However, identifying these expression quantitative trait loci (eQTLs) is complicated…

Co-varying neighborhood analysis identifies cell populations associated with phenotypes of interest from single-cell transcriptomics.

Author(s): Reshef YA, Rumker L, Kang JB, Nathan A, Korsunsky I, Asgari S, Murray MB, Moody DB, Raychaudhuri SJournal: Nat BiotechnolPMID: 34675423 October 2021

As single-cell datasets grow in sample size, there is a critical need to characterize cell states that vary across samples…

Modeling memory T cell states at single-cell resolution identifies in vivo state-dependence of eQTLs influencing disease

Author(s): Nathan A, Asgari S, Ishigaki K, Amariuta T, Luo Y, Beynor JI, Baglaenko Y, Suliman S, Price A, Lecca L, Murray MB, Moody DB, Raychaudhuri SJournal: bioRxiv July 2021

Many non-coding genetic variants cause disease by modulating gene expression. However, identifying these expression quantitative trait loci (eQTLs) is complicated…

Multimodally profiling memory T cells from a tuberculosis cohort identifies cell state associations with demographics, environment and disease.

Author(s): Nathan A, Beynor JI, Baglaenko Y, Suliman S, Ishigaki K, Asgari S, Huang CC, Luo Y, Zhang Z, Lopez K, Lindestam Arlehamn CS, Ernst JD, Jimenez J, Calderón RI, Lecca L, Van Rhijn I, Moody DB, Murray MB, Raychaudhuri SJournal: Nat ImmunolPMID: 34031617 May 2021

Multimodal T cell profiling can enable more precise characterization of elusive cell states underlying disease. Here, we integrated single-cell RNA…

Axes of inter-sample variability among transcriptional neighborhoods reveal disease associated cell states in single-cell data

Author(s): Reshef YA, Rumker L, Kang JB, Nathan A, Murray MB, Moody DB, Raychaudhuri SJournal: bioRxiv April 2021

As single-cell datasets grow in sample size, there is a critical need to characterize cell states that vary across samples…