Delly

Delly is an integrated structural variant (SV) and copy-number variant (CNV) prediction method that can discover, genotype and visualize deletions, insertions, tandem duplications, inversions and translocations at single-nucleotide resolution in short-read and long-read whole-genome sequencing data. It uses paired-ends, split-reads and read-depth to discover and genotype SVs in the genome.

Installing Delly

Delly is available as a pre-compiled binary, a singularity container (SIF file), a docker container or via Bioconda. You can also build Delly from source:

git clone --recursive https://github.com/dellytools/delly.git && cd delly/ && make all

Running Delly

Delly needs a sorted, indexed and duplicate marked BAM or CRAM file for every input sample. An indexed reference genome is required to identify split-reads and to decode CRAM files.

Short-read SV discovery

delly sr -g ref.fa input.bam > delly.vcf

You can also redirect the output to a BCF file.

delly sr -o delly.bcf -g ref.fa input.bam

bcftools view delly.bcf > delly.vcf

Long-read SV discovery

For Oxford Nanopore sequencing data:

delly lr -y ont -o delly.bcf -g hg38.fa input.bam

For PacBio sequencing data:

delly lr -y pb -o delly.bcf -g hg38.fa input.bam

Assembly-based SV discovery

For a haplotype-resolved assembly:

delly asm -y diploid -g hg38.fa s1.h1.bam s1.h2.bam s2.h1.bam s2.h2.bam ...

For a so-called squashed assembly:

delly asm -y squashed -g hg38.fa s1.bam s2.bam ...

Somatic SV calling

Somatic SV calling is available for short-reads (subcommand: sr) and long-reads (subcommand: lr).

• At least one tumor sample and a matched control sample are required for SV discovery

delly [sr|lr] -o t1.bcf -g hg38.fa tumor1.bam control1.bam

• Somatic filtering requires a tab-delimited sample description file where the first column is the sample id (as in the VCF/BCF file) and the second column is either tumor or control.

delly filter -f somatic -o t1.somatic.bcf -s samples.tsv t1.bcf

• You can also use a larger panel of normal for somatic SV filtering

delly [sr|lr] -o t1.bcf -g hg38.fa tumor1.bam control1.bam ... controlN.bam

Germline SV calling

Germline SV calling is available for short-reads (subcommand: sr) and long-reads (subcommand: lr).

• SV discovery is done by sample for high-coverage genomes

delly [sr|lr] -g hg38.fa -o s1.bcf sample1.bam

• Merge SV sites into an SV site list

delly merge -o sites.bcf s1.bcf s2.bcf ... sN.bcf

• Genotype this merged SV site list across all samples in parallel

delly [sr|lr] -g hg38.fa -v sites.bcf -o s1.geno.bcf s1.bam

delly [sr|lr] -g hg38.fa -v sites.bcf -o sN.geno.bcf sN.bam

• Merge all genotyped samples to get a single VCF/BCF using bcftools. This can be done in chunks if necessary.

bcftools merge -m id -O b -o merged.bcf s1.geno.bcf s2.geno.bcf ... sN.geno.bcf

• Apply the germline SV filter

delly filter -f germline -o germline.bcf merged.bcf

CNV calling

delly cnv is a whole-genome read-depth method with GC-bias and mappability correction. Whole-exome or targeted data are not supported. You can generate read-depth profiles with delly using

delly cnv -g hg38.fa -c out.cov.gz -o out.bcf -u out.seg.bed input.bam

The output file out.cov.gz and the segmentation out.seg.bed can be plotted using R

Rscript R/rd.R out.cov.gz out.seg.bed

Instead of the segmentation, you can also visualize the CNV calls.

bcftools query -f "%CHROM\t%POS\t%INFO/END\t%ID[\t%RDCN]\n" out.bcf > seg.bed

Rscript R/rd.R out.cov.gz seg.bed

Germline CNV calling

Germline CNV calling can be done using short- or long-reads using this workflow.

• Call CNVs for each sample

delly cnv -o c1.bcf -g hg38.fa input.bam

• Merge CNVs into a unified CNV site list

delly merge -e -o sites.bcf c1.bcf c2.bcf ... cN.bcf

• Genotype CNVs for each sample

delly cnv -v sites.bcf -g hg38.fa -o geno1.bcf input.bam

• Merge genotypes using bcftools

bcftools merge -m id -O b -o merged.bcf geno1.bcf ... genoN.bcf

• Apply the germline CNV filter

delly filter -f germline -o germline.bcf merged.bcf

• Optional: Plot copy-number distributions for large number of samples (>>100)

bcftools query -f "%ID[\t%RDCN]\n" germline.bcf > plot.tsv

Rscript R/cnv.R plot.tsv

Somatic copy-number alterations (SCNAs)

• CNVs are first called on the tumor genome. Depending on the coverage and tumor purity you can adapt the minimum CNV size (-z) and the sample purity (-p) which affect the sensitivity of SCNA detection.

delly cnv -o tumor.bcf -c tumor.cov.gz -g hg38.fa tumor.bam

• Then these CNVs are genotyped in the control sample.

delly cnv -v tumor.bcf -o control.bcf -g hg38.fa control.bam

• You can then merge both files using bcftools.

bcftools merge -m id -O b -o tumor_control.bcf tumor.bcf control.bcf

• Somatic filtering requires a tab-delimited sample description file where the first column is the sample id (as in the VCF/BCF file) and the second column is either tumor or control.

delly filter -p -f somatic -o somatic.bcf -s samples.tsv tumor_control.bcf

• Optional: Plot the SCNAs using bcftools and R.

bcftools query -s tumor -f "%CHROM\t%POS\t%INFO/END\t%ID[\t%RDCN]\n" somatic.bcf > segmentation.bed

Rscript R/rd.R tumor.cov.gz segmentation.bed

Examples

Some small examples are included for short-read, long-read and copy-number variant calling.

delly sr -g example/ref.fa -o sr.bcf example/sr.bam

delly lr -g example/ref.fa -o lr.bcf example/lr.bam

delly cnv -g example/ref.fa -c out.cov.gz -o cnv.bcf example/sr.bam

More in-depth tutorials for SV calling are available here:

• Short-read SV calling: https://github.com/tobiasrausch/vc

• Long-read SV calling: https://github.com/tobiasrausch/sv

Alternate alignments for genome graphs

Instead of providing only one input alignment, delly supports now multiple alternate alignments on different linear reference genomes using minimap2 or pan-genome graphs using minigraph.

minimap2 -ax map-pb -L chm13.fa sample.fq.gz
minigraph --vc -cx lr pangenome.gfa.gz sample.fq.gz

If the above alignment files are then stored as sample.chm13.bam and sample.gaf.gz you can use a simple tab-delimited config file for all alternate alignments with delly.

cat align.config

sample.chm13.bam   chm13.fa
sample.gaf.gz   pangenome.gfa.gz

delly lr -y pb -o delly.bcf -g hg38.fa -l align.config sample.hg38.bam

Structural variants are still reported with respect to GRCh38 coordinates but the output will only contain SVs that are not present in any of the alternate alignments. Please note that many pangenome graphs contain only SVs greater 50bp so you need to filter the above delly output to match the size range.

bcftools view -i '(QUAL>=300) && ( ((SVTYPE=="INS") && (INFO/SVLEN>50)) || (SVTYPE=="BND") || ((INFO/END - POS)>50) )' delly.bcf

Please note that for inter-chromosomal translocations, delly uses INFO/CHR2 for the second chromosome. You can convert an inter-chromosomal translocation to the two-record breakend format using:

python scripts/delly2bnd.py -v delly.bcf -r hg38.fa -o delly.bnd.bcf

FAQ

• Visualization of SVs
  You may want to try out wally to plot candidate structural variants. The paired-end coloring is explained in wally's README file.

• Can Delly be used on a non-diploid genome?
  The SV site discovery works for any ploidy. However, Delly's genotyping model assumes a ploidy of 2. The CNV calling allows to set the baseline ploidy on the command-line.

• Delly is running too slowly what can I do?
  For short-reads, you should exclude telomere and centromere regions and also all unplaced contigs (-x command-line option). In addition, you can filter input reads more stringently using -q 20 and -s 15. Lastly, -z can be set to 5 for high-coverage data.

• What pre-processing of BAM/CRAM files is required? BAM/CRAM files need to be sorted, indexed and ideally duplicate marked.

• Usage/discussion mailing list?
  There is a delly discussion group delly-users.

Citation

Tobias Rausch, Thomas Zichner, Andreas Schlattl, Adrian M. Stuetz, Vladimir Benes, Jan O. Korbel.
DELLY: structural variant discovery by integrated paired-end and split-read analysis.
Bioinformatics. 2012 Sep 15;28(18):i333-i339.
https://doi.org/10.1093/bioinformatics/bts378

License

Delly is distributed under the BSD 3-Clause license. Consult the accompanying LICENSE file for more details.

Credits

HTSlib is heavily used for all genomic alignment and variant processing. Boost for various data structures and algorithms. Claude for bug fixes, performance improvements and code suggestions. arfer for annotating SVs and Edlib for pairwise alignments.