NanoCov

NanoCov is a high-performance tool for calculating and visualizing genomic coverage from BAM files. It's designed to efficiently process large datasets and generate publication-quality plots of per-base coverage across chromosomes.

Coverage Visualization

NanoCov provides high-quality coverage visualization for individual chromosomes with features including:

• Per-base coverage plots with adaptive binning
• Support for logarithmic and linear scaling
• Multiple color themes (Catppuccin, Nord, Gruvbox)
• Publication-ready PNG and SVG output formats
• Detect chromosomal aneuploidy or large structural variations

The plot automatically sorts chromosomes in natural order (1-22, X, Y, MT) and color-codes coverage levels using a gradient color scheme that highlights variations.

Per-Chromosome Detailed View

For in-depth analysis, NanoCov generates detailed per-chromosome plots with comprehensive statistics:

These detailed plots include:

• Per-base coverage profile with color gradient indicating coverage depth
• Read statistics panel showing N50, quality metrics, and length distribution
• Coverage statistics including mean, median, and standard deviation
• Automatic binning for optimal visualization of regions of any size

Features

• Fast: Parallel processing of BAM files for high throughput
• Flexible: Analyze whole genomes or specific regions defined by BED files
• Informative: Detailed statistics including mean, median, N50, and more
• Visual: Publication-quality plots with multiple color themes
• Scalable: Handles large genomes with adaptive binning
• Versatile: Supports both per-chromosome and genome-wide visualizations
• Insightful: Extracts meaningful statistics including N50, mean/median coverage

Installation

From Source

cargo install --git https://github.com/geonic/nanocov

Requirements

• Rust 1.85 or newer (edition 2024)
• Samtools (for BAM indexing)

Quick Start

# Index your BAM file (if not already indexed)
samtools index your_data.bam

# Run basic coverage analysis
nanocov -i your_data.bam --output-dir results

# Analyze specific regions from a BED file
nanocov -i your_data.bam -b regions.bed --output-dir results

# Generate per-chromosome plots (disabled by default)
nanocov -i your_data.bam --per-chromosome-plot --output-dir results

# Use linear scale for plots (log scale is default)
nanocov -i your_data.bam --per-chromosome-plot --linear --output-dir results

# Generate statistics output (always enabled)
nanocov -i your_data.bam --output-dir results

Usage

USAGE:
    nanocov (--input <FILE> | --batch-tsv <FILE>) --output-dir <DIR> [OPTIONS]

OPTIONS:
    -i, --input <FILE>         Input BAM file
    --batch-tsv <FILE>         TSV with BAM path, BED path, and optional prefix columns
    --batch-output <FILE>      Output file for aggregated batch statistics [default: <output-dir>/batch.statistics.tsv]
    -b, --bed <FILE>           BED file with regions to include (0-based, end-exclusive)
    -o, --output-dir <DIR>     Output directory for generated files
    --prefix <STRING>          Output file prefix [default: input file stem]
    -t, --threads <NUM>        Worker threads (alias for --async-tasks)
    --async-tasks <NUM>        Number of async tasks [default: half of available cores, minimum 2]
    --io-buffer-size <KB>      Async I/O buffer size in KB [default: 64]
    -c, --chunk-size <NUM>     Chunk size for region processing in base pairs [default: 100000]
    --adaptive-chunks          Use adaptive chunk sizing based on region length
    --mmap                     Enable memory-mapped file I/O
    --theme <THEME>            Color theme [latte, frappe, nord, gruvbox]
    --svg                      Use SVG output format for plots
    --plot-bin-size <NUM>      Fixed plot bin size in bp (overrides adaptive plot binning)
    --show-zeros               Show regions with zero coverage in plots
    --linear                   Use linear scale for coverage plots
    --overview-plot            Generate the overview plot
    --per-chromosome-plot      Generate per-chromosome plots
    --non-canonical            Include non-canonical chromosomes in coverage statistics (default: canonical + MT/EBV)
    --invert-regions           Invert BED regions (analyze the complement within each chromosome)
    --sequential-plots         Generate plots sequentially (concurrent is default)
    -h, --help                 Print help information

Outputs

For an input file example.bam and output option -o results, NanoCov always produces:

• results/example.tsv: Tab-separated coverage data for each position
• results/example.statistics: Statistics output file

Optional plot outputs:

• results/example.<chrom>.png (or .svg) when --per-chromosome-plot is enabled
• results/example.overview.png (or .svg) when --overview-plot is enabled

Color Themes

NanoCov supports multiple color themes to create publication-quality figures that match your preferences:

Available Themes

Below is a representation of how the different themes appear in the plots:

To use a specific theme:

nanocov -i your_data.bam --per-chromosome-plot --theme frappe --output-dir results

The example images above show the visual differences between the themes. Choose the one that best fits your needs.

Generating Theme Examples

You can easily generate examples with all four themes using these commands:

# Generate examples with sample data for all themes
nanocov -i your_data.bam --per-chromosome-plot --theme latte --output-dir results
nanocov -i your_data.bam --per-chromosome-plot --theme frappe --output-dir results
nanocov -i your_data.bam --per-chromosome-plot --theme nord --output-dir results
nanocov -i your_data.bam --per-chromosome-plot --theme gruvbox --output-dir results

Each theme creates distinct visualizations that may be better suited for different publication contexts or personal preferences.

Advanced Usage

Analyzing Specific Regions

Use a BED file to limit coverage analysis to regions of interest (0-based, end-exclusive):

nanocov -i sample.bam -b targets.bed --output-dir results

Generating Statistics Output

Generate detailed statistics for quality control:

nanocov -i sample.bam --output-dir results

This will create a file called sample.statistics with statistics including:

• Number of alignments/reads
• Yield statistics (total and >25kb)
• N50 and N75 values
• Length statistics (mean, median)
• Mean coverage
• File metadata (path, creation time)

Statistics output is always written to <output-dir>/<prefix>.statistics.

Logarithmic Scale (Default)

Logarithmic scale is the default for plots and works well for highly variable coverage:

nanocov -i sample.bam --per-chromosome-plot --output-dir results

This is particularly useful when analyzing regions with very different coverage depths (e.g., comparing high-coverage exons to lower-coverage introns).

Custom Themes

Select a theme that works best for your publication or presentation:

nanocov -i sample.bam --per-chromosome-plot --theme nord --output-dir results

Batch Mode (TSV)

Run multiple BAM/BED pairs in one command using --batch-tsv. The TSV has three columns: BAM path, BED path, and an optional prefix to use for that sample's outputs (use -/none/NA to omit a BED for a sample).

Example samples.tsv:

/data/sample1.bam	/data/targets1.bed	sample1
/data/sample2.bam	-	sample2

Command:

nanocov --batch-tsv samples.tsv --output-dir results

NanoCov will process each row, using the row-specific BED (or none if omitted), and write a combined table to results/batch.statistics.tsv with prefix and bed_path columns prepended. Individual outputs use the row prefix if provided; otherwise a unique prefix is derived from the BAM name (with numeric suffixes to avoid collisions).

Examples

Basic Coverage Analysis

nanocov -i your_data.bam --output-dir results

This generates:

• A tabular TSV file with per-base coverage data for downstream analysis
• A statistics summary file (.statistics)

Targeted Analysis with Enhanced Visualization

nanocov -i your_data.bam -b regions.bed --per-chromosome-plot --theme frappe --show-zeros --output-dir results

This analyzes only the regions in your BED file. Add --per-chromosome-plot (and/or --overview-plot) to generate themed plots and include zero-coverage regions.

License

MIT

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.