Machine-Assisted Mixed Sample Analysis for Scalable Disease Screening

The uploaded dataset consists of raw FASTQ files generated within the study "Machine-Assisted Mixed Sample Analysis for Scalable Disease Screening." Sequencing was performed using the Illumina MiSeq platform with paired-end reads (2×151 bp) following targeted enrichment of genes associated with hereditary disease predisposition.
The dataset was designed to evaluate machine-assisted and computational approaches for the analysis of pooled biological samples in large-scale disease screening applications. It includes sequencing data from various pooling strategies, such as pooled whole blood, buffy coat fractions, isolated DNA samples, and pooled post-amplification products, together with individually processed control samples.
The primary aim of the dataset is to facilitate the development and validation of bioinformatic pipelines for variant calling, allele frequency estimation, and detection sensitivity assessment in mixed samples. The dataset further supports research into scalable and cost-efficient screening methodologies applicable to preventive and population-level diagnostics.
All sequencing data were anonymized prior to publication and contain no personally identifiable information. The dataset is intended for reuse in bioinformatics, genomic screening optimization, and computational diagnostic research.