The dataset contains processed T-cell receptor repertoire sequencing data from 79 individuals of different sex and age, originally published in [1] and [2]. Note that [1] describes only a subset of samples, while [2] describes the full cohort. The libraries were prepared using a 5'RACE protocol and sequenced on HiSEQ. The libraries incorporate unique molecular identifier (UMI) tags that were mainly used for counting cDNA molecules. Preprocessing was performed using the MIGEC software [3] as follows: all UMI tags represented by a single sequencing read were discarded, the remaining UMI tags were used to assemble cDNA consensus sequences. Note that this procedure eliminates most of cross-sample contamination (batch effect) as described in [2]. VDJ partitioning and CDR3 extraction was performed using MiTCR software [4], sequencing error correction was performed using ETE option in MiTCR. All datasets are converted into VDJtools [5] format, see http://vdjtools-doc.readthedocs.io/en/latest/input.html#vdjtools-format. Sample description: The A* in sample identifier is the batch ID. Age and sex data is provided in the metadata.txt file. Samples having age "0" are umbilical cord blood samples. Contributors: The T-cell repertoire aging study was a project ran in the Genomics of Adaptive Immunity Lab (Prof. Dmitry Chudakov) The samples were acquired, prepared and sequenced by Dr. Olga Britanova The data was analyzed and uploaded by Dr. Mikhail Shugay Citations: [1] OV Britanova, EV Putintseva, M Shugay, EM Merzlyak, MA Turchaninova, et al. Age-related decrease in TCR repertoire diversity measured with deep and normalized sequence profiling. The Journal of Immunology 2014; 192 (6), 2689-2698 [2] OV Britanova, M Shugay, EM Merzlyak, DB Staroverov, EV Putintseva, et al. Dynamics of individual T cell repertoires: from cord blood to centenarians. The Journal of Immunology 2016; 196 (12), 5005-5013 [3] M Shugay, OV Britanova, EM Merzlyak, MA Turchaninova, IZ Mamedov, et al. Towards error-free profiling of immune repertoires. Nature methods 2014; 11 (6), 653-655 [4] DA Bolotin, M Shugay, IZ Mamedov, EV Putintseva, MA Turchaninova, et al. MiTCR: software for T-cell receptor sequencing data analysis. Nature methods 2013; 10 (9), 813-814 [5] M Shugay, DV Bagaev, MA Turchaninova, DA Bolotin, OV Britanova, et al. VDJtools: unifying post-analysis of T cell receptor repertoires. PLoS computational biology 2015; 11 (11), e1004503