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9: Structural Variant Discovery & Copy Number Alterations

1 min read • Verified October 2026 • Peer-Reviewed Learning Resource
Tested Stacks: GATK 4.6.1 Samtools 1.21 Nextflow 24.10 Seurat v5.1 Python 3.12
Prerequisites: Basic Linux CLI & Sequencing Formats
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Chapter 9: Structural Variant Discovery & Copy Number Alterations

While single nucleotide variants account for the largest count of mutations, Structural Variants (SVs)—defined as genomic alterations affecting 50 base pairs or more—encompass vastly more altered nucleotides per human genome. SVs drive human diversity, evolutionary adaptations, and severe genetic diseases including autism, congenital heart defects, and oncogenic gene fusions.

The Three Signatures of Structural Variation in Short Reads

Alignments contain three complementary signals that reveal SVs:

  • Discordant Read Pairs: Paired-end reads whose mapped distance differs significantly from the expected library insert size, or whose relative orientation is abnormal (e.g., both mapping to the reverse strand, signaling an inversion).
  • Split Reads: Reads that span the exact breakpoint of an SV. Part of the read maps to one locus, while the remainder maps to a distant locus (indicated by soft clipping S in the CIGAR string).
  • Read Depth Variation: Deletions show a 50% (heterozygous) or 100% (homozygous) drop in local coverage, while duplications exhibit a commensurate coverage increase.

1. Short-Read SV Calling with Manta

# Configure and execute Manta for germline SV discovery
configManta.py \
    --bam sample1.recalibrated.bam \
    --referenceFasta GRCh38.fasta \
    --runDir manta_output/

# Execute workflow on 16 CPU cores
python3 manta_output/runWorkflow.py -m local -j 16

2. Long-Read Resolution with Sniffles2

Long reads easily span repetitive elements and segmental duplications that blind short reads. Sniffles2 resolves complex SVs, telomeric repeats, and mobile element insertions (LINE-1, Alu) with single-base breakpoint precision:

# Call SVs from PacBio HiFi or ONT BAM
sniffles \
    --input pacbio_aligned.bam \
    --vcf pacbio_svs.vcf.gz \
    --reference GRCh38.fasta \
    --threads 16
⚠️

Common Pitfalls & Troubleshooting Checklist

  • Java Heap Exhaustion (GATK / Picard): If processes terminate with java.lang.OutOfMemoryError, set your environment variable explicitly: export _JAVA_OPTIONS="-Xmx16g -Djava.io.tmpdir=/tmp".
  • Index Timestamp Mismatch: If tools complain that a BAM index is missing or out of date, regenerate with samtools index -@ 4 sample.bam.
  • Conda Channel Conflicts: Avoid ABI incompatibilities between bioconda and conda-forge by setting strict priority: conda config --set channel_priority strict.
  • Chromosome Naming Contamination: Always verify whether reference FASTA headers use chr1 or 1; divergent naming causes silent alignment drops.
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