Dataset Open Access

Dynamics of individual T cell repertoires: from cord blood to centenarians

Genomics of Adaptive Immunity Laboratory

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  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.826447", 
  "author": [
      "family": "Genomics of Adaptive Immunity Laboratory"
  "issued": {
    "date-parts": [
  "abstract": "<p>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.</p>\n\n<p>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.\u00a0Preprocessing 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\u00a0</p>\n\n<p><strong>Sample description:</strong></p>\n\n<ul>\n\t<li>The A* in sample identifier is the batch ID.</li>\n\t<li>Age and sex data is provided in the metadata.txt file.</li>\n\t<li>Samples having age \"0\" are umbilical cord blood samples.</li>\n</ul>\n\n<p><strong>Contributors:</strong></p>\n\n<ul>\n\t<li>The T-cell repertoire aging study was a project ran in the Genomics of Adaptive Immunity Lab (Prof. Dmitry Chudakov)</li>\n\t<li>The samples were acquired, prepared and sequenced by Dr. Olga Britanova</li>\n\t<li>The data was analyzed and uploaded by Dr. Mikhail Shugay</li>\n</ul>\n\n<p><strong>Citations:</strong></p>\n\n<ul>\n\t<li>[1]\u00a0OV Britanova, EV Putintseva, M Shugay, EM Merzlyak, MA Turchaninova, et al.\u00a0Age-related decrease in TCR repertoire diversity\u00a0measured with deep and normalized sequence profiling.\u00a0The Journal of Immunology 2014;\u00a0192 (6), 2689-2698</li>\n\t<li>[2]\u00a0OV Britanova, M Shugay, EM Merzlyak, DB Staroverov, EV Putintseva, et al.\u00a0Dynamics of individual T cell repertoires: from cord blood to centenarians.\u00a0The Journal of Immunology 2016; 196 (12), 5005-5013</li>\n\t<li>[3]\u00a0M Shugay, OV Britanova, EM Merzlyak, MA Turchaninova, IZ Mamedov, et al.\u00a0Towards error-free profiling of immune repertoires.\u00a0Nature methods 2014; 11 (6), 653-655</li>\n\t<li>[4]\u00a0DA Bolotin, M Shugay, IZ Mamedov, EV Putintseva, MA Turchaninova, et al.\u00a0MiTCR: software for T-cell receptor sequencing data analysis.\u00a0Nature methods 2013; 10 (9), 813-814</li>\n\t<li>[5]\u00a0M Shugay, DV Bagaev, MA Turchaninova, DA Bolotin, OV Britanova, et al.\u00a0VDJtools: unifying post-analysis of T cell receptor repertoires.\u00a0PLoS computational biology 2015; 11 (11), e1004503</li>\n</ul>", 
  "title": "Dynamics of individual T cell repertoires: from cord blood to centenarians", 
  "type": "dataset", 
  "id": "826447"
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