Smart Data Approaches to Mixed Sample Screening: A Pilot Study in Disease Detection

The uploaded dataset contains raw next-generation sequencing (NGS) data in FASTQ format generated as part of the pilot study "Smart Data Approaches to Mixed Sample Screening: A Pilot Study in Disease Detection." The dataset comprises paired-end sequencing reads obtained using the Illumina MiSeq platform following targeted amplification of clinically relevant genes associated with hereditary disease susceptibility.
The study focuses on the application of data-driven and bioinformatic approaches for improving mixed sample screening strategies and enhancing the efficiency of variant detection in pooled biological material. Multiple pooling methodologies were evaluated, including pooling at the whole blood, buffy coat, isolated DNA, and post-PCR product levels, alongside individually sequenced reference samples.
The dataset is intended to support reproducibility of analyses related to allele frequency estimation, low-frequency variant detection, and optimization of computational workflows for scalable disease screening. All samples were fully anonymized prior to sequencing, and the dataset contains no directly identifiable personal information. The data may be reused for methodological, bioinformatic, and translational research in pooled sequencing and precision diagnostics.