LONGO

LONGO quantifies gene length-dependent expression to assess neuronal identity by computing long gene expression metrics from RNA-seq and microarray data.

Key Features:

• Gene Length-Based Analysis: Leverages neuronal enrichment of long genes (>100 kilobases from transcription start to end) to detect neuron-specific expression patterns.
• Long Gene Quotient (LQ): Implements the Long Gene Quotient (LQ) metric to quantify long gene expression (LGE) for single-cell and population-level analyses.
• Input Data Types: Operates on RNA-seq and microarray expression data to compute LQ and related LGE measurements.
• Implementation: Implemented as an R package for computation of LQ and analysis of long-gene expression signatures.
• Neuronal Identity Assessment: Provides quantitative LGE measurements to validate neuronal identity, including during cellular reprogramming experiments.

Scientific Applications:

• Validation of Neuronal Differentiation and Reprogramming: Uses LQ and LGE measurements to distinguish neurons from non-neuronal cells and validate neuronal identity during differentiation and reprogramming.
• Single-Cell and Population-Level Assessment: Applies to single-cell and bulk population RNA-seq or microarray studies for assessing neuronal identity via long-gene expression.
• Neuronal Development and Disease Modeling: Supports studies of neuronal development and disease modeling that rely on cellular reprogramming and gene-expression-based identity assessment.

Methodology:

Implemented as an R package that computes the Long Gene Quotient (LQ) by quantifying expression of long genes (>100 kilobases from transcription start to end) in RNA-seq or microarray data.