534 lines
18 KiB
Markdown
534 lines
18 KiB
Markdown
# deepTools Complete Tool Reference
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This document provides a comprehensive reference for all deepTools command-line utilities organized by category.
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## BAM and bigWig File Processing Tools
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### multiBamSummary
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Computes read coverages for genomic regions across multiple BAM files, outputting compressed numpy arrays for downstream correlation and PCA analysis.
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**Modes:**
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- **bins**: Genome-wide analysis using consecutive equal-sized windows (default 10kb)
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- **BED-file**: Restricts analysis to user-specified genomic regions
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**Key Parameters:**
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- `--bamfiles, -b`: Indexed BAM files (space-separated, required)
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- `--outFileName, -o`: Output coverage matrix file (required)
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- `--BED`: Region specification file (BED-file mode only)
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- `--binSize`: Window size in bases (default: 10,000)
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- `--labels`: Custom sample identifiers
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- `--minMappingQuality`: Quality threshold for read inclusion
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- `--numberOfProcessors, -p`: Parallel processing cores
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- `--extendReads`: Fragment size extension
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- `--ignoreDuplicates`: Remove PCR duplicates
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- `--outRawCounts`: Export tab-delimited file with coordinate columns and per-sample counts
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**Output:** Compressed numpy array (.npz) for plotCorrelation and plotPCA
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**Common Usage:**
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```bash
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# Genome-wide comparison
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multiBamSummary bins --bamfiles sample1.bam sample2.bam -o results.npz
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# Peak region comparison
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multiBamSummary BED-file --BED peaks.bed --bamfiles sample1.bam sample2.bam -o results.npz
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```
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---
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### multiBigwigSummary
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Similar to multiBamSummary but operates on bigWig files instead of BAM files. Used for comparing coverage tracks across samples.
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**Modes:**
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- **bins**: Genome-wide analysis
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- **BED-file**: Region-specific analysis
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**Key Parameters:** Similar to multiBamSummary but accepts bigWig files
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---
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### bamCoverage
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Converts BAM alignment files into normalized coverage tracks in bigWig or bedGraph formats. Calculates coverage as number of reads per bin.
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**Key Parameters:**
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- `--bam, -b`: Input BAM file (required)
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- `--outFileName, -o`: Output filename (required)
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- `--outFileFormat, -of`: Output type (bigwig or bedgraph)
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- `--normalizeUsing`: Normalization method
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- **RPKM**: Reads Per Kilobase per Million mapped reads
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- **CPM**: Counts Per Million mapped reads
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- **BPM**: Bins Per Million mapped reads
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- **RPGC**: Reads per genomic content (requires --effectiveGenomeSize)
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- **None**: No normalization (default)
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- `--effectiveGenomeSize`: Mappable genome size (required for RPGC)
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- `--binSize`: Resolution in base pairs (default: 50)
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- `--extendReads, -e`: Extend reads to fragment length (recommended for ChIP-seq, NOT for RNA-seq)
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- `--centerReads`: Center reads at fragment length for sharper signals
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- `--ignoreDuplicates`: Count identical reads only once
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- `--minMappingQuality`: Filter reads below quality threshold
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- `--minFragmentLength / --maxFragmentLength`: Fragment length filtering
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- `--smoothLength`: Window averaging for noise reduction
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- `--MNase`: Analyze MNase-seq data for nucleosome positioning
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- `--Offset`: Position-specific offsets (useful for RiboSeq, GROseq)
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- `--filterRNAstrand`: Separate forward/reverse strand reads
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- `--ignoreForNormalization`: Exclude chromosomes from normalization (e.g., sex chromosomes)
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- `--numberOfProcessors, -p`: Parallel processing
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**Important Notes:**
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- For RNA-seq: Do NOT use --extendReads (would extend over splice junctions)
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- For ChIP-seq: Use --extendReads with smaller bin sizes
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- Never apply --ignoreDuplicates after GC bias correction
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**Common Usage:**
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```bash
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# Basic coverage with RPKM normalization
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bamCoverage --bam input.bam --outFileName coverage.bw --normalizeUsing RPKM
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# ChIP-seq with extension
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bamCoverage --bam chip.bam --outFileName chip_coverage.bw \
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--binSize 10 --extendReads 200 --ignoreDuplicates
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# Strand-specific RNA-seq
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bamCoverage --bam rnaseq.bam --outFileName forward.bw \
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--filterRNAstrand forward
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```
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---
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### bamCompare
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Compares two BAM files by generating bigWig or bedGraph files, normalizing for sequencing depth differences. Processes genome in equal-sized bins and performs per-bin calculations.
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**Comparison Methods:**
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- **log2** (default): Log2 ratio of samples
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- **ratio**: Direct ratio calculation
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- **subtract**: Difference between files
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- **add**: Sum of samples
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- **mean**: Average across samples
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- **reciprocal_ratio**: Negative inverse for ratios < 0
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- **first/second**: Output scaled signal from single file
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**Normalization Methods:**
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- **readCount** (default): Compensates for sequencing depth
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- **SES**: Selective enrichment statistics
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- **RPKM**: Reads per kilobase per million
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- **CPM**: Counts per million
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- **BPM**: Bins per million
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- **RPGC**: Reads per genomic content (requires --effectiveGenomeSize)
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**Key Parameters:**
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- `--bamfile1, -b1`: First BAM file (required)
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- `--bamfile2, -b2`: Second BAM file (required)
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- `--outFileName, -o`: Output filename (required)
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- `--outFileFormat`: bigwig or bedgraph
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- `--operation`: Comparison method (see above)
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- `--scaleFactorsMethod`: Normalization method (see above)
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- `--binSize`: Bin width for output (default: 50bp)
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- `--pseudocount`: Avoid division by zero (default: 1)
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- `--extendReads`: Extend reads to fragment length
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- `--ignoreDuplicates`: Count identical reads once
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- `--minMappingQuality`: Quality threshold
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- `--numberOfProcessors, -p`: Parallelization
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**Common Usage:**
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```bash
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# Log2 ratio of treatment vs control
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bamCompare -b1 treatment.bam -b2 control.bam -o log2ratio.bw
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# Subtract control from treatment
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bamCompare -b1 treatment.bam -b2 control.bam -o difference.bw \
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--operation subtract --scaleFactorsMethod readCount
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```
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---
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### correctGCBias / computeGCBias
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**computeGCBias:** Identifies GC-content bias from sequencing and PCR amplification.
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**correctGCBias:** Corrects BAM files for GC bias detected by computeGCBias.
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**Key Parameters (computeGCBias):**
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- `--bamfile, -b`: Input BAM file
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- `--effectiveGenomeSize`: Mappable genome size
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- `--genome, -g`: Reference genome in 2bit format
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- `--fragmentLength, -l`: Fragment length (for single-end)
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- `--biasPlot`: Output diagnostic plot
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**Key Parameters (correctGCBias):**
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- `--bamfile, -b`: Input BAM file
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- `--effectiveGenomeSize`: Mappable genome size
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- `--genome, -g`: Reference genome in 2bit format
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- `--GCbiasFrequenciesFile`: Frequencies from computeGCBias
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- `--correctedFile, -o`: Output corrected BAM
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**Important:** Never use --ignoreDuplicates after GC bias correction
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---
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### alignmentSieve
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Filters BAM files by various quality metrics on-the-fly. Useful for creating filtered BAM files for specific analyses.
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**Key Parameters:**
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- `--bam, -b`: Input BAM file
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- `--outFile, -o`: Output BAM file
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- `--minMappingQuality`: Minimum mapping quality
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- `--ignoreDuplicates`: Remove duplicates
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- `--minFragmentLength / --maxFragmentLength`: Fragment length filters
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- `--samFlagInclude / --samFlagExclude`: SAM flag filtering
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- `--shift`: Shift reads (e.g., for ATACseq Tn5 correction)
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- `--ATACshift`: Automatically shift for ATAC-seq data
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---
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### computeMatrix
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Calculates scores per genomic region and prepares matrices for plotHeatmap and plotProfile. Processes bigWig score files and BED/GTF region files.
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**Modes:**
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- **reference-point**: Signal distribution relative to specific position (TSS, TES, or center)
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- **scale-regions**: Signal across regions standardized to uniform lengths
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**Key Parameters:**
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- `-R`: Region file(s) in BED/GTF format (required)
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- `-S`: BigWig score file(s) (required)
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- `-o`: Output matrix file (required)
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- `-b`: Upstream distance from reference point
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- `-a`: Downstream distance from reference point
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- `-m`: Region body length (scale-regions only)
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- `-bs, --binSize`: Bin size for averaging scores
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- `--skipZeros`: Skip regions with all zeros
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- `--minThreshold / --maxThreshold`: Filter by signal intensity
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- `--sortRegions`: ascending, descending, keep, no
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- `--sortUsing`: mean, median, max, min, sum, region_length
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- `-p, --numberOfProcessors`: Parallel processing
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- `--averageTypeBins`: Statistical method (mean, median, min, max, sum, std)
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**Output Options:**
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- `--outFileNameMatrix`: Export tab-delimited data
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- `--outFileSortedRegions`: Save filtered/sorted BED file
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**Common Usage:**
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```bash
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# TSS analysis
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computeMatrix reference-point -S signal.bw -R genes.bed \
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-o matrix.gz -b 2000 -a 2000 --referencePoint TSS
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# Scaled gene body
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computeMatrix scale-regions -S signal.bw -R genes.bed \
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-o matrix.gz -b 1000 -a 1000 -m 3000
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```
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---
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## Quality Control Tools
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### plotFingerprint
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Quality control tool primarily for ChIP-seq experiments. Assesses whether antibody enrichment was successful. Generates cumulative read coverage profiles to distinguish signal from noise.
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**Key Parameters:**
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- `--bamfiles, -b`: Indexed BAM files (required)
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- `--plotFile, -plot, -o`: Output image filename (required)
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- `--extendReads, -e`: Extend reads to fragment length
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- `--ignoreDuplicates`: Count identical reads once
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- `--minMappingQuality`: Mapping quality filter
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- `--centerReads`: Center reads at fragment length
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- `--minFragmentLength / --maxFragmentLength`: Fragment filters
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- `--outRawCounts`: Save per-bin read counts
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- `--outQualityMetrics`: Output QC metrics (Jensen-Shannon distance)
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- `--labels`: Custom sample names
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- `--numberOfProcessors, -p`: Parallel processing
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**Interpretation:**
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- Ideal control: Straight diagonal line
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- Strong ChIP: Steep rise towards highest rank (concentrated reads in few bins)
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- Weak enrichment: Flatter curve approaching diagonal
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**Common Usage:**
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```bash
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plotFingerprint -b input.bam chip1.bam chip2.bam \
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--labels Input ChIP1 ChIP2 -o fingerprint.png \
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--extendReads 200 --ignoreDuplicates
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```
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---
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### plotCoverage
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Visualizes average read distribution across the genome. Shows genome coverage and helps determine if sequencing depth is adequate.
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**Key Parameters:**
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- `--bamfiles, -b`: BAM files to analyze (required)
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- `--plotFile, -o`: Output plot filename (required)
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- `--ignoreDuplicates`: Remove PCR duplicates
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- `--minMappingQuality`: Quality threshold
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- `--outRawCounts`: Save underlying data
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- `--labels`: Sample names
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- `--numberOfSamples`: Number of positions to sample (default: 1,000,000)
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---
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### bamPEFragmentSize
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Determines fragment length distribution for paired-end sequencing data. Essential QC to verify expected fragment sizes from library preparation.
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**Key Parameters:**
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- `--bamfiles, -b`: BAM files (required)
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- `--histogram, -hist`: Output histogram filename (required)
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- `--plotTitle, -T`: Plot title
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- `--maxFragmentLength`: Maximum length to consider (default: 1000)
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- `--logScale`: Use logarithmic Y-axis
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- `--outRawFragmentLengths`: Save raw fragment lengths
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---
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### plotCorrelation
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Analyzes sample correlations from multiBamSummary or multiBigwigSummary outputs. Shows how similar different samples are.
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**Correlation Methods:**
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- **Pearson**: Measures metric differences; sensitive to outliers; appropriate for normally distributed data
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- **Spearman**: Rank-based; less influenced by outliers; better for non-normal distributions
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**Visualization Options:**
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- **heatmap**: Color intensity with hierarchical clustering (complete linkage)
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- **scatterplot**: Pairwise scatter plots with correlation coefficients
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**Key Parameters:**
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- `--corData, -in`: Input matrix from multiBamSummary/multiBigwigSummary (required)
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- `--corMethod`: pearson or spearman (required)
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- `--whatToShow`: heatmap or scatterplot (required)
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- `--plotFile, -o`: Output filename (required)
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- `--skipZeros`: Exclude zero-value regions
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- `--removeOutliers`: Use median absolute deviation (MAD) filtering
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- `--outFileCorMatrix`: Export correlation matrix
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- `--labels`: Custom sample names
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- `--plotTitle`: Plot title
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- `--colorMap`: Color scheme (50+ options)
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- `--plotNumbers`: Display correlation values on heatmap
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**Common Usage:**
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```bash
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# Heatmap with Pearson correlation
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plotCorrelation -in readCounts.npz --corMethod pearson \
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--whatToShow heatmap -o correlation_heatmap.png --plotNumbers
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# Scatterplot with Spearman correlation
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plotCorrelation -in readCounts.npz --corMethod spearman \
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--whatToShow scatterplot -o correlation_scatter.png
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```
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---
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### plotPCA
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Generates principal component analysis plots from multiBamSummary or multiBigwigSummary output. Displays sample relationships in reduced dimensionality.
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**Key Parameters:**
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- `--corData, -in`: Coverage file from multiBamSummary/multiBigwigSummary (required)
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- `--plotFile, -o`: Output image (png, eps, pdf, svg) (required)
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- `--outFileNameData`: Export PCA data (loadings/rotation and eigenvalues)
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- `--labels, -l`: Custom sample labels
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- `--plotTitle, -T`: Plot title
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- `--plotHeight / --plotWidth`: Dimensions in centimeters
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- `--colors`: Custom symbol colors
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- `--markers`: Symbol shapes
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- `--transpose`: Perform PCA on transposed matrix (rows=samples)
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- `--ntop`: Use top N variable rows (default: 1000)
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- `--PCs`: Components to plot (default: 1 2)
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- `--log2`: Log2-transform data before analysis
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- `--rowCenter`: Center each row at 0
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**Common Usage:**
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```bash
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plotPCA -in readCounts.npz -o PCA_plot.png \
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-T "PCA of read counts" --transpose
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```
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---
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## Visualization Tools
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### plotHeatmap
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Creates genomic region heatmaps from computeMatrix output. Generates publication-quality visualizations.
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**Key Parameters:**
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- `--matrixFile, -m`: Matrix from computeMatrix (required)
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- `--outFileName, -o`: Output image (png, eps, pdf, svg) (required)
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- `--outFileSortedRegions`: Save regions after filtering
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- `--outFileNameMatrix`: Export matrix values
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- `--interpolationMethod`: auto, nearest, bilinear, bicubic, gaussian
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- Default: nearest (≤1000 columns), bilinear (>1000 columns)
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- `--dpi`: Figure resolution
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**Clustering:**
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- `--kmeans`: k-means clustering
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- `--hclust`: Hierarchical clustering (slower for >1000 regions)
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- `--silhouette`: Calculate cluster quality metrics
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**Visual Customization:**
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- `--heatmapHeight / --heatmapWidth`: Dimensions (3-100 cm)
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- `--whatToShow`: plot, heatmap, colorbar (combinations)
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- `--alpha`: Transparency (0-1)
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- `--colorMap`: 50+ color schemes
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- `--colorList`: Custom gradient colors
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- `--zMin / --zMax`: Intensity scale limits
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- `--boxAroundHeatmaps`: yes/no (default: yes)
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**Labels:**
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- `--xAxisLabel / --yAxisLabel`: Axis labels
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- `--regionsLabel`: Region set identifiers
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- `--samplesLabel`: Sample names
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- `--refPointLabel`: Reference point label
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- `--startLabel / --endLabel`: Region boundary labels
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**Common Usage:**
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```bash
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# Basic heatmap
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plotHeatmap -m matrix.gz -o heatmap.png
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# With clustering and custom colors
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plotHeatmap -m matrix.gz -o heatmap.png \
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--kmeans 3 --colorMap RdBu --zMin -3 --zMax 3
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```
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---
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### plotProfile
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Generates profile plots showing scores across genomic regions using computeMatrix output.
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**Key Parameters:**
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- `--matrixFile, -m`: Matrix from computeMatrix (required)
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- `--outFileName, -o`: Output image (png, eps, pdf, svg) (required)
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- `--plotType`: lines, fill, se, std, overlapped_lines, heatmap
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- `--colors`: Color palette (names or hex codes)
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- `--plotHeight / --plotWidth`: Dimensions in centimeters
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- `--yMin / --yMax`: Y-axis range
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- `--averageType`: mean, median, min, max, std, sum
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**Clustering:**
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- `--kmeans`: k-means clustering
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- `--hclust`: Hierarchical clustering
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- `--silhouette`: Cluster quality metrics
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**Labels:**
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- `--plotTitle`: Main heading
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- `--regionsLabel`: Region set identifiers
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- `--samplesLabel`: Sample names
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- `--startLabel / --endLabel`: Region boundary labels (scale-regions mode)
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**Output Options:**
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- `--outFileNameData`: Export data as tab-separated values
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- `--outFileSortedRegions`: Save filtered/sorted regions as BED
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**Common Usage:**
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```bash
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# Line plot
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plotProfile -m matrix.gz -o profile.png --plotType lines
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# With standard error shading
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plotProfile -m matrix.gz -o profile.png --plotType se \
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--colors blue red green
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```
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---
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### plotEnrichment
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Calculates and visualizes signal enrichment across genomic regions. Measures percentage of alignments overlapping region groups. Useful for FRiP (Fragment in Peaks) scores.
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**Key Parameters:**
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- `--bamfiles, -b`: Indexed BAM files (required)
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- `--BED`: Region files in BED/GTF format (required)
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- `--plotFile, -o`: Output visualization (png, pdf, eps, svg)
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- `--labels, -l`: Custom sample identifiers
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- `--outRawCounts`: Export numerical data
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- `--perSample`: Group by sample instead of feature (default)
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- `--regionLabels`: Custom region names
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**Read Processing:**
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- `--minFragmentLength / --maxFragmentLength`: Fragment filters
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- `--minMappingQuality`: Quality threshold
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- `--samFlagInclude / --samFlagExclude`: SAM flag filters
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- `--ignoreDuplicates`: Remove duplicates
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- `--centerReads`: Center reads for sharper signal
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**Common Usage:**
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```bash
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plotEnrichment -b Input.bam H3K4me3.bam \
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--BED peaks_up.bed peaks_down.bed \
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--regionLabels "Up regulated" "Down regulated" \
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-o enrichment.png
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```
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---
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## Miscellaneous Tools
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### computeMatrixOperations
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Advanced matrix manipulation tool for combining or subsetting matrices from computeMatrix. Enables complex multi-sample, multi-region analyses.
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**Operations:**
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- `cbind`: Combine matrices column-wise
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- `rbind`: Combine matrices row-wise
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- `subset`: Extract specific samples or regions
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- `filterStrand`: Keep only regions on specific strand
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- `filterValues`: Apply signal intensity filters
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- `sort`: Order regions by various criteria
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- `dataRange`: Report min/max values
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**Common Usage:**
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```bash
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# Combine matrices
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computeMatrixOperations cbind -m matrix1.gz matrix2.gz -o combined.gz
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|
|
|
# Extract specific samples
|
|
computeMatrixOperations subset -m matrix.gz --samples 0 2 -o subset.gz
|
|
```
|
|
|
|
---
|
|
|
|
### estimateReadFiltering
|
|
|
|
Predicts the impact of various filtering parameters without actually filtering. Helps optimize filtering strategies before running full analyses.
|
|
|
|
**Key Parameters:**
|
|
- `--bamfiles, -b`: BAM files to analyze
|
|
- `--sampleSize`: Number of reads to sample (default: 100,000)
|
|
- `--binSize`: Bin size for analysis
|
|
- `--distanceBetweenBins`: Spacing between sampled bins
|
|
|
|
**Filtration Options to Test:**
|
|
- `--minMappingQuality`: Test quality thresholds
|
|
- `--ignoreDuplicates`: Assess duplicate impact
|
|
- `--minFragmentLength / --maxFragmentLength`: Test fragment filters
|
|
|
|
---
|
|
|
|
## Common Parameters Across Tools
|
|
|
|
Many deepTools commands share these filtering and performance options:
|
|
|
|
**Read Filtering:**
|
|
- `--ignoreDuplicates`: Remove PCR duplicates
|
|
- `--minMappingQuality`: Filter by alignment confidence
|
|
- `--samFlagInclude / --samFlagExclude`: SAM format filtering
|
|
- `--minFragmentLength / --maxFragmentLength`: Fragment length bounds
|
|
|
|
**Performance:**
|
|
- `--numberOfProcessors, -p`: Enable parallel processing
|
|
- `--region`: Process specific genomic regions (chr:start-end)
|
|
|
|
**Read Processing:**
|
|
- `--extendReads`: Extend to fragment length
|
|
- `--centerReads`: Center at fragment midpoint
|
|
- `--ignoreDuplicates`: Count unique reads only
|