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A large-scale database of T-cell receptor beta (TCRβ) sequences and binding associations from natural and synthetic exposure to SARS-CoV-2.

Sean NolanMarissa VignaliMark KlingerJennifer N DinesIan M KaplanEmily SvejnohaTracy CraftKatie BolandMitch PeseskyRachel M GittelmanThomas M SnyderChristopher J GooleySimona SempriniClaudio CerchioneMassimiliano MazzaOttavia M DelmonteKerry DobbsGonzalo Carreño-TarragonaSantiago BarrioVittorio SambriGiovanni MartinelliJason D GoldmanJames R HeathLuigi D NotarangeloJonathan M CarlsonJoaquin Martinez-LopezHarlan S Robins
Published in: Research square (2020)
We describe the establishment and current content of the ImmuneCODE™ database, which includes hundreds of millions of T-cell Receptor (TCR) sequences from over 1,400 subjects exposed to or infected with the SARS-CoV-2 virus, as well as over 135,000 high-confidence SARS-CoV-2-specific TCRs. This database is made freely available, and the data contained in it can be downloaded and analyzed online or offline to assist with the global efforts to understand the immune response to the SARS-CoV-2 virus and develop new interventions.
Keyphrases
  • sars cov
  • respiratory syndrome coronavirus
  • adverse drug
  • physical activity
  • electronic health record
  • healthcare
  • immune response
  • deep learning
  • big data
  • coronavirus disease
  • machine learning
  • artificial intelligence