Numanagic, IbrahimBonfield, James K.Hach, FarazVoges, JanOstermann, JoernAlberti, ClaudioMattavelli, MarcoSahinalp, Cenk2016-12-012016-12-012016-12-01201610.1038/nmeth.4037https://infoscience.epfl.ch/handle/20.500.14299/131725WOS:000389133000019High-throughput sequencing (HTS) data are commonly stored as raw sequencing reads in FASTQ format or as reads mapped to a reference, in SAM format, both with large memory footprints. Worldwide growth of HTS data has prompted the development of compression methods that aim to significantly reduce HTS data size. Here we report on a benchmarking study of available compression methods on a comprehensive set of HTS data using an automated framework.high throughput genome sequencinggenomic data compressiongenome compressiontext::journal::journal article::research article