Fig. 1: Overview of the workflow for adaptive sampling using nanopore sequencing. | npj Genomic Medicine

Fig. 1: Overview of the workflow for adaptive sampling using nanopore sequencing.

From: Assessing the efficacy of target adaptive sampling long-read sequencing through hereditary cancer patient genomes

Fig. 1: Overview of the workflow for adaptive sampling using nanopore sequencing.

The FAST5 files were base-called using highaccuracy model in Guppy, followed by alignment of all FASTQ files using minimap2. De novo detection of SNVs/Indels were performed through PEPPER-Margin-DeepVariant, while SVs were identified using nanomonsv. Common SNP genotypes were called using GLIMPSE. For downstream analysis, the polygenic risk score was calculated with PLINK using genotyping results obtained from GLIMPSE. In allele-specific methylation analysis, each read in the BAM file was assigned to its respective haplotype using WhatsHap, based on the genotyping results obtained from GLIMPSE. The methylation calling for each haplotype was performed using f5c, and the identification of aberrantly methylated genes was performed using an in-house script.

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