DNA sequencing is a big data science that is rapidly increasing in volume and complexity. This frustrates data acquisition, storage, distribution and analysis. GENALICE has developed an ultra-fast, highly accurate and very cost-effective new Next Generation Sequencing (NGS) data processing solution: GENALICE MAP. An important cornerstone of this breakthrough solution is the GENALICE Aligned Reads (GAR) format to reduce the storage footprint of aligned NGS reads. The GAR format is based on three key methods: reference backed encoding, base quality score binning and best reference scores. This results in a file format that is only a fraction of the size of current formats (FASTQ/BAM). Using independent read alignments (BWA-MEM) and variant calling (GATK, VarScan and Platypus) tools, we further show that our methods to reduce the storage footprint are solid and improve variant detection accuracy. We conclude that the GAR format lowers NGS data storage costs and leverages datadistribution and analysis.