Detecting T cell receptors involved in immune responses from single repertoire snapshots.

Hypervariable T cell receptors (TCRs) play a key role in adaptive immunity, recognizing a vast diversity of pathogen-derived antigens. Our ability to extract clinically relevant information from large high-throughput sequencing of TCR repertoires (RepSeq) data is limited, because little is known abo...
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Gespeichert in:

Autor*in:	Mikhail V Pogorelyy [verfasserIn] Anastasia A Minervina [verfasserIn] Mikhail Shugay [verfasserIn] Dmitriy M Chudakov [verfasserIn] Yuri B Lebedev [verfasserIn] Thierry Mora [verfasserIn] Aleksandra M Walczak [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Übergeordnetes Werk:	In: PLoS Biology - Public Library of Science (PLoS), 2003, 17(2019), 6, p e3000314
Übergeordnetes Werk:	volume:17 ; year:2019 ; number:6, p e3000314

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.1371/journal.pbio.3000314

Katalog-ID:	DOAJ059698527

Internformat


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520			\|a Hypervariable T cell receptors (TCRs) play a key role in adaptive immunity, recognizing a vast diversity of pathogen-derived antigens. Our ability to extract clinically relevant information from large high-throughput sequencing of TCR repertoires (RepSeq) data is limited, because little is known about TCR-disease associations. We present Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences (ALICE), a statistical approach that identifies TCR sequences actively involved in current immune responses from a single RepSeq sample and apply it to repertoires of patients with a variety of disorders - patients with autoimmune disease (ankylosing spondylitis [AS]), under cancer immunotherapy, or subject to an acute infection (live yellow fever [YF] vaccine). We validate the method with independent assays. ALICE requires no longitudinal data collection nor large cohorts, and it is directly applicable to most RepSeq datasets. Its results facilitate the identification of TCR variants associated with diseases and conditions, which can be used for diagnostics and rational vaccine design.
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912			\|a GBV_ILN_206
912			\|a GBV_ILN_213
912			\|a GBV_ILN_230
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2001
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912			\|a GBV_ILN_2048
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Indexfelder

author_variant	m v p mvp a a m aam m s ms d m c dmc y b l ybl t m tm a m w amw
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publishDate	2019
allfields	10.1371/journal.pbio.3000314 doi (DE-627)DOAJ059698527 (DE-599)DOAJf13a9335fc074698b5d77df7658e6bb9 DE-627 ger DE-627 rakwb eng QH301-705.5 Mikhail V Pogorelyy verfasserin aut Detecting T cell receptors involved in immune responses from single repertoire snapshots. 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Hypervariable T cell receptors (TCRs) play a key role in adaptive immunity, recognizing a vast diversity of pathogen-derived antigens. Our ability to extract clinically relevant information from large high-throughput sequencing of TCR repertoires (RepSeq) data is limited, because little is known about TCR-disease associations. We present Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences (ALICE), a statistical approach that identifies TCR sequences actively involved in current immune responses from a single RepSeq sample and apply it to repertoires of patients with a variety of disorders - patients with autoimmune disease (ankylosing spondylitis [AS]), under cancer immunotherapy, or subject to an acute infection (live yellow fever [YF] vaccine). We validate the method with independent assays. ALICE requires no longitudinal data collection nor large cohorts, and it is directly applicable to most RepSeq datasets. Its results facilitate the identification of TCR variants associated with diseases and conditions, which can be used for diagnostics and rational vaccine design. Biology (General) Anastasia A Minervina verfasserin aut Mikhail Shugay verfasserin aut Dmitriy M Chudakov verfasserin aut Yuri B Lebedev verfasserin aut Thierry Mora verfasserin aut Aleksandra M Walczak verfasserin aut In PLoS Biology Public Library of Science (PLoS), 2003 17(2019), 6, p e3000314 (DE-627)373755597 (DE-600)2126773-X 15457885 nnns volume:17 year:2019 number:6, p e3000314 https://doi.org/10.1371/journal.pbio.3000314 kostenfrei https://doaj.org/article/f13a9335fc074698b5d77df7658e6bb9 kostenfrei https://doi.org/10.1371/journal.pbio.3000314 kostenfrei https://doaj.org/toc/1544-9173 Journal toc kostenfrei https://doaj.org/toc/1545-7885 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2019 6, p e3000314
spelling	10.1371/journal.pbio.3000314 doi (DE-627)DOAJ059698527 (DE-599)DOAJf13a9335fc074698b5d77df7658e6bb9 DE-627 ger DE-627 rakwb eng QH301-705.5 Mikhail V Pogorelyy verfasserin aut Detecting T cell receptors involved in immune responses from single repertoire snapshots. 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Hypervariable T cell receptors (TCRs) play a key role in adaptive immunity, recognizing a vast diversity of pathogen-derived antigens. Our ability to extract clinically relevant information from large high-throughput sequencing of TCR repertoires (RepSeq) data is limited, because little is known about TCR-disease associations. We present Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences (ALICE), a statistical approach that identifies TCR sequences actively involved in current immune responses from a single RepSeq sample and apply it to repertoires of patients with a variety of disorders - patients with autoimmune disease (ankylosing spondylitis [AS]), under cancer immunotherapy, or subject to an acute infection (live yellow fever [YF] vaccine). We validate the method with independent assays. ALICE requires no longitudinal data collection nor large cohorts, and it is directly applicable to most RepSeq datasets. Its results facilitate the identification of TCR variants associated with diseases and conditions, which can be used for diagnostics and rational vaccine design. Biology (General) Anastasia A Minervina verfasserin aut Mikhail Shugay verfasserin aut Dmitriy M Chudakov verfasserin aut Yuri B Lebedev verfasserin aut Thierry Mora verfasserin aut Aleksandra M Walczak verfasserin aut In PLoS Biology Public Library of Science (PLoS), 2003 17(2019), 6, p e3000314 (DE-627)373755597 (DE-600)2126773-X 15457885 nnns volume:17 year:2019 number:6, p e3000314 https://doi.org/10.1371/journal.pbio.3000314 kostenfrei https://doaj.org/article/f13a9335fc074698b5d77df7658e6bb9 kostenfrei https://doi.org/10.1371/journal.pbio.3000314 kostenfrei https://doaj.org/toc/1544-9173 Journal toc kostenfrei https://doaj.org/toc/1545-7885 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2019 6, p e3000314
allfields_unstemmed	10.1371/journal.pbio.3000314 doi (DE-627)DOAJ059698527 (DE-599)DOAJf13a9335fc074698b5d77df7658e6bb9 DE-627 ger DE-627 rakwb eng QH301-705.5 Mikhail V Pogorelyy verfasserin aut Detecting T cell receptors involved in immune responses from single repertoire snapshots. 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Hypervariable T cell receptors (TCRs) play a key role in adaptive immunity, recognizing a vast diversity of pathogen-derived antigens. Our ability to extract clinically relevant information from large high-throughput sequencing of TCR repertoires (RepSeq) data is limited, because little is known about TCR-disease associations. We present Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences (ALICE), a statistical approach that identifies TCR sequences actively involved in current immune responses from a single RepSeq sample and apply it to repertoires of patients with a variety of disorders - patients with autoimmune disease (ankylosing spondylitis [AS]), under cancer immunotherapy, or subject to an acute infection (live yellow fever [YF] vaccine). We validate the method with independent assays. ALICE requires no longitudinal data collection nor large cohorts, and it is directly applicable to most RepSeq datasets. Its results facilitate the identification of TCR variants associated with diseases and conditions, which can be used for diagnostics and rational vaccine design. Biology (General) Anastasia A Minervina verfasserin aut Mikhail Shugay verfasserin aut Dmitriy M Chudakov verfasserin aut Yuri B Lebedev verfasserin aut Thierry Mora verfasserin aut Aleksandra M Walczak verfasserin aut In PLoS Biology Public Library of Science (PLoS), 2003 17(2019), 6, p e3000314 (DE-627)373755597 (DE-600)2126773-X 15457885 nnns volume:17 year:2019 number:6, p e3000314 https://doi.org/10.1371/journal.pbio.3000314 kostenfrei https://doaj.org/article/f13a9335fc074698b5d77df7658e6bb9 kostenfrei https://doi.org/10.1371/journal.pbio.3000314 kostenfrei https://doaj.org/toc/1544-9173 Journal toc kostenfrei https://doaj.org/toc/1545-7885 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2019 6, p e3000314
allfieldsGer	10.1371/journal.pbio.3000314 doi (DE-627)DOAJ059698527 (DE-599)DOAJf13a9335fc074698b5d77df7658e6bb9 DE-627 ger DE-627 rakwb eng QH301-705.5 Mikhail V Pogorelyy verfasserin aut Detecting T cell receptors involved in immune responses from single repertoire snapshots. 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Hypervariable T cell receptors (TCRs) play a key role in adaptive immunity, recognizing a vast diversity of pathogen-derived antigens. Our ability to extract clinically relevant information from large high-throughput sequencing of TCR repertoires (RepSeq) data is limited, because little is known about TCR-disease associations. We present Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences (ALICE), a statistical approach that identifies TCR sequences actively involved in current immune responses from a single RepSeq sample and apply it to repertoires of patients with a variety of disorders - patients with autoimmune disease (ankylosing spondylitis [AS]), under cancer immunotherapy, or subject to an acute infection (live yellow fever [YF] vaccine). We validate the method with independent assays. ALICE requires no longitudinal data collection nor large cohorts, and it is directly applicable to most RepSeq datasets. Its results facilitate the identification of TCR variants associated with diseases and conditions, which can be used for diagnostics and rational vaccine design. Biology (General) Anastasia A Minervina verfasserin aut Mikhail Shugay verfasserin aut Dmitriy M Chudakov verfasserin aut Yuri B Lebedev verfasserin aut Thierry Mora verfasserin aut Aleksandra M Walczak verfasserin aut In PLoS Biology Public Library of Science (PLoS), 2003 17(2019), 6, p e3000314 (DE-627)373755597 (DE-600)2126773-X 15457885 nnns volume:17 year:2019 number:6, p e3000314 https://doi.org/10.1371/journal.pbio.3000314 kostenfrei https://doaj.org/article/f13a9335fc074698b5d77df7658e6bb9 kostenfrei https://doi.org/10.1371/journal.pbio.3000314 kostenfrei https://doaj.org/toc/1544-9173 Journal toc kostenfrei https://doaj.org/toc/1545-7885 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2019 6, p e3000314
allfieldsSound	10.1371/journal.pbio.3000314 doi (DE-627)DOAJ059698527 (DE-599)DOAJf13a9335fc074698b5d77df7658e6bb9 DE-627 ger DE-627 rakwb eng QH301-705.5 Mikhail V Pogorelyy verfasserin aut Detecting T cell receptors involved in immune responses from single repertoire snapshots. 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Hypervariable T cell receptors (TCRs) play a key role in adaptive immunity, recognizing a vast diversity of pathogen-derived antigens. Our ability to extract clinically relevant information from large high-throughput sequencing of TCR repertoires (RepSeq) data is limited, because little is known about TCR-disease associations. We present Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences (ALICE), a statistical approach that identifies TCR sequences actively involved in current immune responses from a single RepSeq sample and apply it to repertoires of patients with a variety of disorders - patients with autoimmune disease (ankylosing spondylitis [AS]), under cancer immunotherapy, or subject to an acute infection (live yellow fever [YF] vaccine). We validate the method with independent assays. ALICE requires no longitudinal data collection nor large cohorts, and it is directly applicable to most RepSeq datasets. Its results facilitate the identification of TCR variants associated with diseases and conditions, which can be used for diagnostics and rational vaccine design. Biology (General) Anastasia A Minervina verfasserin aut Mikhail Shugay verfasserin aut Dmitriy M Chudakov verfasserin aut Yuri B Lebedev verfasserin aut Thierry Mora verfasserin aut Aleksandra M Walczak verfasserin aut In PLoS Biology Public Library of Science (PLoS), 2003 17(2019), 6, p e3000314 (DE-627)373755597 (DE-600)2126773-X 15457885 nnns volume:17 year:2019 number:6, p e3000314 https://doi.org/10.1371/journal.pbio.3000314 kostenfrei https://doaj.org/article/f13a9335fc074698b5d77df7658e6bb9 kostenfrei https://doi.org/10.1371/journal.pbio.3000314 kostenfrei https://doaj.org/toc/1544-9173 Journal toc kostenfrei https://doaj.org/toc/1545-7885 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2019 6, p e3000314
language	English
source	In PLoS Biology 17(2019), 6, p e3000314 volume:17 year:2019 number:6, p e3000314
sourceStr	In PLoS Biology 17(2019), 6, p e3000314 volume:17 year:2019 number:6, p e3000314
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Biology (General)
isfreeaccess_bool	true
container_title	PLoS Biology
authorswithroles_txt_mv	Mikhail V Pogorelyy @@aut@@ Anastasia A Minervina @@aut@@ Mikhail Shugay @@aut@@ Dmitriy M Chudakov @@aut@@ Yuri B Lebedev @@aut@@ Thierry Mora @@aut@@ Aleksandra M Walczak @@aut@@
publishDateDaySort_date	2019-01-01T00:00:00Z
hierarchy_top_id	373755597
id	DOAJ059698527
language_de	englisch
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callnumber-first	Q - Science
author	Mikhail V Pogorelyy
spellingShingle	Mikhail V Pogorelyy misc QH301-705.5 misc Biology (General) Detecting T cell receptors involved in immune responses from single repertoire snapshots.
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topic_title	QH301-705.5 Detecting T cell receptors involved in immune responses from single repertoire snapshots
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title	Detecting T cell receptors involved in immune responses from single repertoire snapshots.
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title_full	Detecting T cell receptors involved in immune responses from single repertoire snapshots
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author_browse	Mikhail V Pogorelyy Anastasia A Minervina Mikhail Shugay Dmitriy M Chudakov Yuri B Lebedev Thierry Mora Aleksandra M Walczak
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title_sort	detecting t cell receptors involved in immune responses from single repertoire snapshots
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title_auth	Detecting T cell receptors involved in immune responses from single repertoire snapshots.
abstract	Hypervariable T cell receptors (TCRs) play a key role in adaptive immunity, recognizing a vast diversity of pathogen-derived antigens. Our ability to extract clinically relevant information from large high-throughput sequencing of TCR repertoires (RepSeq) data is limited, because little is known about TCR-disease associations. We present Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences (ALICE), a statistical approach that identifies TCR sequences actively involved in current immune responses from a single RepSeq sample and apply it to repertoires of patients with a variety of disorders - patients with autoimmune disease (ankylosing spondylitis [AS]), under cancer immunotherapy, or subject to an acute infection (live yellow fever [YF] vaccine). We validate the method with independent assays. ALICE requires no longitudinal data collection nor large cohorts, and it is directly applicable to most RepSeq datasets. Its results facilitate the identification of TCR variants associated with diseases and conditions, which can be used for diagnostics and rational vaccine design.
abstractGer	Hypervariable T cell receptors (TCRs) play a key role in adaptive immunity, recognizing a vast diversity of pathogen-derived antigens. Our ability to extract clinically relevant information from large high-throughput sequencing of TCR repertoires (RepSeq) data is limited, because little is known about TCR-disease associations. We present Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences (ALICE), a statistical approach that identifies TCR sequences actively involved in current immune responses from a single RepSeq sample and apply it to repertoires of patients with a variety of disorders - patients with autoimmune disease (ankylosing spondylitis [AS]), under cancer immunotherapy, or subject to an acute infection (live yellow fever [YF] vaccine). We validate the method with independent assays. ALICE requires no longitudinal data collection nor large cohorts, and it is directly applicable to most RepSeq datasets. Its results facilitate the identification of TCR variants associated with diseases and conditions, which can be used for diagnostics and rational vaccine design.
abstract_unstemmed	Hypervariable T cell receptors (TCRs) play a key role in adaptive immunity, recognizing a vast diversity of pathogen-derived antigens. Our ability to extract clinically relevant information from large high-throughput sequencing of TCR repertoires (RepSeq) data is limited, because little is known about TCR-disease associations. We present Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences (ALICE), a statistical approach that identifies TCR sequences actively involved in current immune responses from a single RepSeq sample and apply it to repertoires of patients with a variety of disorders - patients with autoimmune disease (ankylosing spondylitis [AS]), under cancer immunotherapy, or subject to an acute infection (live yellow fever [YF] vaccine). We validate the method with independent assays. ALICE requires no longitudinal data collection nor large cohorts, and it is directly applicable to most RepSeq datasets. Its results facilitate the identification of TCR variants associated with diseases and conditions, which can be used for diagnostics and rational vaccine design.
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title_short	Detecting T cell receptors involved in immune responses from single repertoire snapshots.
url	https://doi.org/10.1371/journal.pbio.3000314 https://doaj.org/article/f13a9335fc074698b5d77df7658e6bb9 https://doaj.org/toc/1544-9173 https://doaj.org/toc/1545-7885
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Detecting T cell receptors involved in immune responses from single repertoire snapshots.

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