SigTools

SigTools provides visualization and statistical analysis of continuous genomic signals such as short-read coverage and epigenomic marks to support exploration, interpretation, and model development.

Key Features:

• R-based statistical visualization: Generates statistical plots for continuous genomic data across scales including entire chromosomes, whole-genome regions, and localized areas around specific points.
• Distribution plots: Visualizes distribution characteristics of genomic signals to reveal value ranges and skewness.
• Autocorrelation plots: Computes autocorrelation to identify repeat patterns and dependencies within genomic signals.
• Correlation plots: Quantifies and visualizes relationships between different genomic signals.
• Aggregation plots: Summarizes signal behavior across genomic features or regions to reveal average patterns.
• Descriptive statistics: Reports text-based summary statistics to inform model training, refinement, and evaluation.

Scientific Applications:

• Histone modifications analysis: Exploration and validation of short-read coverage and epigenomic mark datasets derived from histone modification profiling.
• Novel chromatin state feature examination: Characterization and interpretation of novel chromatin state signals generated by learning models.

Methodology:

Implemented in R, SigTools computes distribution, autocorrelation, correlation and aggregation plots and produces descriptive statistics from continuous genomic signal inputs (short-read coverage, epigenomic marks).