Optically mapped genomes for 8 different reference human samples were used to construct the internal cohort database for evaluating nanotatoR’s performance. All sample datasets, including “Utah woman” (Genome in a Bottle Consortium sample NA12878), “Ashkenazi family” (NA24143 [or GM24143]: Mother, NA24149 [or GM24149]: Father, and NA24385 [or GM24385]: Son), GM11428 (6-year-old female with duplicated chromosome), GM09888 (8-year-old female with trichorhinophalangeal syndrome), GM08331 (4-year-old with chromosome deletion) and GM06226 (6-year-old male with chromosome 1–16 translocation and associated 16p CNV), were obtained from the Bionano Genomics public datasets (https://bionanogenomics.com/library/datasets/). OGM-based genome assembly and variant calling and annotation were performed using Solve version 3.5 (Bionano Genomics). Subsequently, samples were annotated with nanotatoR to examine the performance.

Additionally, we tested nanotatoR’s ability to accurately annotate the known disease variants in a previously published cohort of 11 Duchenne Muscular Dystrophy samples [27]. For this, internal cohort frequency calculations are based on these 11 samples. For gene expression integration, NA12878 fastq files (RNA-Seq) were obtained from Sequence Read archive (SRA) (Sample GSM754335) and aligned to reference hg19, using STAR [30]. Read counts were estimated using RSEM [31], reported in Transcripts per Million (TPM).

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