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dc.contributor.author
Greiff, Victor
dc.contributor.author
Bhat, Pooja
dc.contributor.author
Cook, Skylar C.
dc.contributor.author
Menzel, Ulrike
dc.contributor.author
Kang, Wenjing
dc.contributor.author
Reddy, Sai T.
dc.date.accessioned
2019-04-17T08:46:28Z
dc.date.available
2017-06-11T18:23:17Z
dc.date.available
2019-04-17T08:46:28Z
dc.date.issued
2015-05-28
dc.identifier.issn
1756-994X
dc.identifier.other
10.1186/s13073-015-0169-8
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/102508
dc.identifier.doi
10.3929/ethz-b-000102508
dc.description.abstract
Background Lymphocyte receptor repertoires are continually shaped throughout the lifetime of an individual in response to environmental and pathogenic exposure. Thus, they may serve as a fingerprint of an individual’s ongoing immunological status (e.g., healthy, infected, vaccinated), with far-reaching implications for immunodiagnostics applications. The advent of high-throughput immune repertoire sequencing now enables the interrogation of immune repertoire diversity in an unprecedented and quantitative manner. However, steadily increasing sequencing depth has revealed that immune repertoires vary greatly among individuals in their composition; correspondingly, it has been reported that there are few shared sequences indicative of immunological status ('public clones'). Disconcertingly, this means that the wealth of information gained from repertoire sequencing remains largely unused for determining the current status of immune responses, thereby hampering the implementation of immune-repertoire-based diagnostics. Methods Here, we introduce a bioinformatics repertoire-profiling framework that possesses the advantage of capturing the diversity and distribution of entire immune repertoires, as opposed to singular public clones. The framework relies on Hill-based diversity profiles composed of a continuum of single diversity indices, which enable the quantification of the extent of immunological information contained in immune repertoires. Results We coupled diversity profiles with unsupervised (hierarchical clustering) and supervised (support vector machine and feature selection) machine learning approaches in order to correlate patients’ immunological statuses with their B- and T-cell repertoire data. We could predict with high accuracy (greater than or equal to 80 %) a wide range of immunological statuses such as healthy, transplantation recipient, and lymphoid cancer, suggesting as a proof of principle that diversity profiling can recover a large amount of immunodiagnostic fingerprints from immune repertoire data. Our framework is highly scalable as it easily allowed for the analysis of 1000 simulated immune repertoires; this exceeds the size of published immune repertoire datasets by one to two orders of magnitude. Conclusions Our framework offers the possibility to advance immune-repertoire-based fingerprinting, which may in the future enable a systems immunogenomics approach for vaccine profiling and the accurate and early detection of disease and infection.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
BioMed Central
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Feature selection
en_US
dc.subject
Chronic Lymphocytic Leukemia
en_US
dc.subject
Influenza vaccination
en_US
dc.subject
Clonal Expansion
en_US
dc.subject
Immunological Status
en_US
dc.title
A bioinformatic framework for immune repertoire diversity profiling enables detection of immunological status
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
ethz.journal.title
Genome Medicine
ethz.journal.volume
7
en_US
ethz.journal.abbreviated
Genome Med
ethz.pages.start
49
en_US
ethz.size
15 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.publication.place
London
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02060 - Dep. Biosysteme / Dep. of Biosystems Science and Eng.::03952 - Reddy, Sai / Reddy, Sai
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02060 - Dep. Biosysteme / Dep. of Biosystems Science and Eng.::03952 - Reddy, Sai / Reddy, Sai
ethz.date.deposited
2017-06-11T18:24:04Z
ethz.source
ECIT
ethz.identifier.importid
imp593653521d6f148722
ethz.ecitpid
pub:160648
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-12T11:34:06Z
ethz.rosetta.lastUpdated
2020-02-15T18:28:59Z
ethz.rosetta.versionExported
true
ethz.COinS
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