lute

lute deconvolutes cell types with varying sizes in bulk RNA-sequencing data by adjusting for differences in cell sizes to improve the accuracy of cell composition estimates.

Key Features:

• Cell size adjustment: Adjusts for differences in cell sizes to improve the accuracy of cell composition estimates rather than estimating the relative fraction of RNA attributable to each cell type.
• Algorithm wrapping framework: Wraps existing deconvolution algorithms in a flexible and extensible framework.
• Benchmarking and comparison: Enables benchmarking and comparison of existing deconvolution algorithms.

Scientific Applications:

• Heterogeneous tissue deconvolution: Estimates cell type proportions in heterogeneous tissues containing cell types with varying cell sizes, such as brain tissue.
• Cell composition control: Controls for cell composition differences across heterogeneous tissue samples in bulk RNA-sequencing data.
• Algorithm enhancement: Enhances and improves existing deconvolution algorithms for broader application to any tissue type with varying cell sizes.

Methodology:

lute wraps existing deconvolution algorithms and adjusts for differences in cell sizes; validation was performed using simulated and real datasets.