ASAP

Autism Susceptibility Analysis Pipeline with focus in Structural Variants.

This repo logs tasks involved for this project- either executed sequentially or asynchronously.

Table of Contents

• Inputs
• QC
  • back-reference-qc
  • ntsm
  • VerifyBamID
  • Somalier
  • Merqury
  • sex-verify
• Genome assembly
• Genome alignment
• Variant calling
• SV merging
• Annotation
• Methylation
• Housekeeping
• Citation

Inputs

Sample origin/cohort

This pertains to SSC + SAGE + Rett-like cohort (189 individuals from 51 families).

Count	Sex (proband-sibling)	Family type
12	F-F	quad
16	F-M	quad
3	M-F	quad
5	M-M	quad
13	F	trio
2	M	trio

Sample sheet is here: /net/eichler/vol28/projects/autism_genome_assembly/nobackups/sample_info.tab

Dataset S1

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QC

back-reference-qc (Kraken2)

• use this pipeline for non-human contamination of reads.
  • minimal requirement: fastq.gz
  • Internal path

ntsm

• use this tool/pipeline to assess inter-sample contamination.
  • minimal requirement: fastq.gz

VerifyBamID

• use this tool/pipeline to assess contamination of non-humanness as well as inter-sample contamination.
  • minimal requirement: bam
  • Internal path

Somalier

• use this tool/pipeline to assess inter-sample contamination as well as ancestry and relatedness.
  • minimal requirement: bam

Merqury

• use this tool/pipeline to assess quality of genome assembly
  • minimal requirement: fastq.gz and its own Illumina
  • Internal path

sex-verify

• use this to check either per cell or sample for sex verification
  • minimal requirement: bam
  • click here for notes

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Genome assembly

This step produces a fasta file.

• hifiasm: use this pipeline/tool to assemble sample genome (trio-phased requires parental Illumina data as input).

• Version used for all our samples: hifiasm 0.16.1 with just HiFi data.

• fix-sex-chromosome: use this pipeline to fix partially phased autism family fathers.

  • Internal path

• Contiguous chromosome X/Y

  • Internal path

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Genome alignment

This step is produces a BAM. And can be achieved via: Internal path

• PacBio_HiFi fastq.gz input, the pipeline uses pbmm2

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Variant calling

• PAV: use hifiasm assembly output for this.(instructions)
• pbsv: use pbmm2 output as input for this.
• Sniffles: use pbmm2 output as input for this.

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SV merging

The steps here are using Truvari by sequential order.

1. Sampleset merge.

bcftools merge --thread {threads} --merge none --force-samples -O z -o {output.vcf.gz} {input.vcf1.gz} {input.vcf2.gz} {input.vcf3.gz}
truvari collapse -i {input.vcf.gz} -c {output.removed.vcf.gz} --sizemin 0 --sizemax 1000000 -k maxqual --gt het --intra --pctseq 0.90 --pctsize 0.90 --refdist 500 | bcftools sort --max-mem 8G -O z -o {output.collapsed.vcf.gz}

2. Inter-sample merge.

bcftools merge --threads {threads} --merge none --force-samples --file-list {input.vcflist} -O z | bcftools norm --threads 15 --do-not-normalize --multiallelics -any --output-type z -o {output.mergevcf.gz}
truvari collapse --input {input.mergevcf.gz} --collapsed-output {output.removed_vcf.gz} --sizemin 0 --sizemax 1000000 --pctseq 0.90 --pctsize 0.90 --keep common --gt all | bcftools sort --max-mem {resources}G --output-type z > {output.collapsed_vcf.gz}

3. Rare SV pool discovery of an example input.

python rareSVpool.py {input.collapsed_sv}

4. De novo validation

• Initial caller support using Truvari
• Callable region evaluation using BoostSV
• Genotyping support using kanpig
• Rare TR expansions/contractions using TRGT
• Multiple sequence alignment (MSA) using MAFFT
• Read-based support validation using subseq or notes here
• Manual inspection using IGV

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Annotation (GRCh38)

• Gene and location annotation using AnnotSV, and then simplified by using sim_annotSV.py
• CADD score using CADD-SV
• Regulatory annotation using REG data and comREG
• Combine all annotations from comREG

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Methylation

This step produces a methylation bed file and bigwig files of the beds. Internal path

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Citation

For citation, please refer to our paper at: https://www.medrxiv.org/content/10.1101/2025.07.21.25331932v1

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