ISLET

ISLET estimates individual-specific and cell-type-specific transcriptome reference panels from repeatedly measured bulk gene expression data to improve signal deconvolution and enable cell-type-specific differential expression analysis.


Key Features:

  • Individual-Specific Reference Panels: Constructs personalized reference panels for subjects with multiple observed samples to improve deconvolution of bulk gene expression data.
  • Cell-Type-Specific Inference: Estimates cell-type-specific reference profiles enabling identification of expression patterns unique to specific cell types.
  • Integration with Mixture Proportions: Integrates personalized reference panels with sample-by-cell-type mixture proportions to enhance accuracy of estimated cell type mixture proportions.
  • Cell-Type-Specific Differential Expression (csDE) Testing: Performs tests to identify cell-type-specific differentially expressed genes.
  • Modeling Repeated Measurements: Models repeatedly measured bulk gene expression to optimize sharing of information within each subject.
  • Required Inputs: Accepts an observed mixture data matrix (features by samples), a sample-by-cell-type mixture proportions matrix, and sample-to-subject mapping information.

Scientific Applications:

  • Longitudinal blood transcriptome studies: Applied to longitudinal transcriptome profiles from blood samples in a large observational study of young children to confirm cell-type-specific gene signatures associated with pancreatic islet autoantibodies.
  • Method validation: Simulation studies validated performance for reference estimation and downstream cell-type-specific differential expression testing.

Methodology:

Models repeatedly measured bulk gene expression using inputs of an observed mixture data matrix (features by samples), a sample-by-cell-type mixture proportions matrix, and sample-to-subject mapping, and optimizes sharing of information within subjects to derive individual- and cell-type-specific reference panels and to conduct cell-type-specific differential expression tests.

Topics

Details

License:
GPL-2.0
Cost:
Free of charge
Tool Type:
library
Operating Systems:
Mac, Linux, Windows
Programming Languages:
R
Added:
1/6/2024
Last Updated:
11/24/2024

Operations

Publications

Feng H, Meng G, Lin T, Parikh H, Pan Y, Li Z, Krischer J, Li Q. ISLET: individual-specific reference panel recovery improves cell-type-specific inference. Genome Biology. 2023;24(1). doi:10.1186/s13059-023-03014-8. PMID:37496087. PMCID:PMC10373385.

PMID: 37496087
Funding: - National Institute of Diabetes and Digestive and Kidney Diseases: U24DK097771 - National Cancer Institute: R03CA270725 - American Cancer Society: IRG-16-186-21