paraphase 0.1.0

paraphase: HiFi-based SMN1/SMN2 variant caller

Paraphase: HiFi-based SMN1/SMN2 variant caller

SMN1, the gene that causes spinal muscular atrophy, is considered a 'dark' region of the genome due to high sequence similarity with its paralog SMN2. Paraphase is a Python tool that takes HiFi BAMs as input (WGS or enrichment), assembles complete SMN1 and SMN2 haplotypes, determines copy numbers and makes phased variant calls for both genes. It also categorizes the haplotypes, enabling future haplotype-based screening of silent carriers (2+0). Please check out our preprint for more details about the method and our population-wide haplotype analysis.

Contact

If you need assistance or have suggestions, please don't hesitate to reach out by email or open a GitHub issue. Xiao Chen: [e-mail]

Dependencies

• samtools
• minimap2
• singularity (if you would like to run DeepVariant and generate vcfs on assembled haplotypes)

Installation

Paraphase can be installed through pip:

pip install paraphase

Alternatively, Paraphase can be installed from GitHub.

git clone https://github.com/PacificBiosciences/paraphase
cd paraphase
python setup.py install

Running the program

paraphase -b input.bam -o output_directory

Alternatively when you have a list of bam files

paraphase -l list.txt -o output_directory

Required parameters:

• -b: Input BAM file or -l: List of BAM files (one per line)
• -o: Output directory

Optional parameters:

• -v: If specified, Paraphase will run DeepVariant to produce VCFs for each haplotype (singularity is required).
• -c: Config file, default config file is paraphase/data/smn1/config.yaml.
• -t: Number of threads, used when -l is specified.
• -d: File listing average genome depth per sample, with two columns, sample ID and depth values, separated by tab or space. This saves run time by skipping the step to calculate genome depth.
• --samtools
• --minimap2
• --singularity

The paths to samtools, minimaps and singularity (only required if -v is specified) can be provided through the --samtools, --minimap2 and --singularity parameters or by modifying the tools section of the config.yaml file.

Note that currently only GRCh38 is supported. We will support GRCh37 in the future if there is request.

Interpreting the output

Paraphase produces a few output files in the directory specified by -o, with the sample ID as the prefix.

• _realigned_tagged.bam: This BAM file can be loaded into IGV for visualization of haplotypes, see the next section.
• If -v is specified, Paraphase will generate VCF files produced by DeepVariant. A VCF file is written for each haplotype, and there is also a _variants.vcf file containing merged variants from all haplotypes. This is a nonstandard scenario with variable ploidy, and we will continue to improve the variant filtering and merging steps. Any suggestions are welcome.
• .json: Main output file, summerizes haplotypes and variant calls for each sample. Details of the fields are explained below:
  • smn1_cn: copy number of SMN1, a null call indicates that Paraphase finds only one haplotype but depth does not unambiguously support a copy number of one or two.
  • smn2_cn: copy number of SMN2, a null call indicates that Paraphase finds only one haplotype but depth does not unambiguously support a copy number of one or two.
  • smn2_del78_cn: copy number of SMN2Δ7–8 (SMN2 with a deletion of Exon7-8)
  • smn1_read_number: number of reads containing c.840C
  • smn2_read_number: number of reads containing c.840T
  • smn2_del78_read_number: number of reads containing the known deletion of Exon7-8 on SMN2
  • smn1_haplotypes: SMN1 haplotypes assembled
  • smn2_haplotypes: SMN2 haplotypes assembled
  • smn2_del78_haplotypes: SMN2Δ7–8 haplotypes assembled
  • two_copy_haplotypes: haplotypes that are present in two copies based on depth. In rare cases two haplotypes are identical and we infer that there exist two of them instead of one by checking the read depth.
  • haplotype_details: lists each haplotype and the variants it contains, followed by the boundary of the region that was resolved on the haplotype, as well as the haplogroup assignment. The variants listed here could be a subset of those called by DeepVariant, as we use a simple pileup method to call variants and we exclude homopolymer regions. For most accurate variant calls, please use the -v option.

Visualizing the output

We can visualize the haplotypes by loading the output file _realigned_tagged.bam into IGV and grouping reads by the HP tag.

In this example, there are two copies of SMN1 and two copies of SMN2. All reads are aligned to SMN1. Reads in blue are uniquely assigned to a haplotype, while reads in gray can be assigned to more than one possible haplotype and a random one is selected (this happens when two haplotypes are identical over a region). The Unassigned category contains reads that carry bases that do not agree with any haplotypes (this could be due to sequencing errors or incompletely assembled haplotypes).

In this second example, smn1hap1 is present in about twice as many reads as the other haplotypes, so Paraphase infers that there are two copies of SMN1 (the haplotype sequences are identical).

The examples folders contains IGV sessions showing more examples.