
Faculty, Staff and Student Publications
Publication Date
7-26-2023
Journal
Genome Biology
Abstract
We propose a statistical framework ISLET to infer individual-specific and cell-type-specific transcriptome reference panels. ISLET models the repeatedly measured bulk gene expression data, to optimize the usage of shared information within each subject. ISLET is the first available method to achieve individual-specific reference estimation in repeated samples. Using simulation studies, we show outstanding performance of ISLET in the reference estimation and downstream cell-type-specific differentially expressed genes testing. We apply ISLET to longitudinal transcriptomes profiled from blood samples in a large observational study of young children and confirm the cell-type-specific gene signatures for pancreatic islet autoantibody. ISLET is available at https://bioconductor.org/packages/ISLET.
Keywords
Child, Humans, Child, Preschool, Islets of Langerhans, Transcriptome, Computer Simulation, Autoantibodies, Gene Expression Profiling, Deconvolution, Temporal measures, Cell-type-specific differential expression, Individual-specific reference panel
DOI
10.1186/s13059-023-03014-8
PMID
37496087
PMCID
PMC10373385
PubMedCentral® Posted Date
7-26-2023
PubMedCentral® Full Text Version
Post-print
Published Open-Access
yes
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Genetic Phenomena Commons, Medical Genetics Commons, Oncology Commons