chromPlot

chromPlot visualizes genomic data along chromosomes to display multiple data tracks (e.g., QTLs, synteny tracts, gene and genetic variant histograms) for error detection and hypothesis generation.

Key Features:

• Chromosomal Contextualization: Displays large and diverse datasets along chromosomes to aid identification of processing errors and anomalies.
• Multi-Track Visualization: Supports simultaneous visualization of multiple data tracks for integrated chromosomal views.
• Versatile Data Representation: Renders data as points, connected lines, colored segments, or histograms to represent continuous and categorical variables.
• Support for Genomic Elements: Displays extensive genomic regions such as Quantitative Trait Loci (QTLs) and synteny tracts alongside histograms of genes and genetic variants.
• Data Input Formats: Accepts input from tables in data.frame and GRanges formats.
• Chromosome Metadata: Includes preloaded chromosomal information for human and mouse and can read Gap and cytoBandIdeo tables from the UCSC Genome Browser.
• R Integration: Implemented as an R package and integrates with genomic data processing packages in R.

Scientific Applications:

• Genomics research: Visualizes genomic distributions and patterns to support analysis of genomic datasets.
• Genetic mapping: Places QTLs and genetic variants in chromosomal context to aid mapping studies.
• Comparative genomics: Displays synteny tracts and large genomic regions for comparative analyses across genomes.
• Data quality control: Facilitates detection of anomalies and errors in genomic data processing via chromosomal visualization.
• Hypothesis generation: Reveals chromosomal patterns that can suggest new biological hypotheses for further study.

Methodology:

Implemented in R, chromPlot reads input in data.frame and GRanges formats (and Gap/cytoBandIdeo tables from the UCSC Genome Browser), organizes data along chromosomes, and renders customizable graphical representations such as points, connected lines, colored segments, and histograms.