DeconRNASeq

DeconRNASeq deconvolves mRNA-Seq expression profiles to estimate relative cell-type proportions in heterogeneous tissue samples.

Key Features:

• Non-Negative Decomposition Algorithm: Employs a globally optimized non-negative decomposition algorithm implemented via quadratic programming to estimate mixing proportions from next-generation sequencing mRNA-Seq data.
• Accuracy and Validation: Validated on in silico mixed mRNA-Seq datasets at known concentrations and benchmark datasets, demonstrating high correlation between predicted and actual tissue fractions.
• Modular Design: Provides modular components that facilitate integration into custom analytical pipelines and adaptation to other high-throughput platforms.
• Implementation: Implemented in R for integration with R-based analysis workflows.

Scientific Applications:

• Tissue Composition Analysis: Quantifies cell-type-specific contributions in bulk mRNA-Seq studies to dissect complex tissue compositions.
• Oncology: Estimates tumor microenvironment cell-type proportions to study tumor heterogeneity.
• Developmental Biology: Resolves changing cell-type proportions during development from bulk expression profiles.
• Immunology: Quantifies immune cell composition in heterogeneous samples to study immune responses.

Methodology:

Performs globally optimized non-negative decomposition using quadratic programming on mRNA-Seq expression matrices; validation employed in silico mixed mRNA-Seq datasets at known concentrations and benchmark datasets.