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Guidelines for using sigQC for systematic evaluation of gene signatures

Abstract:

With the increased use of next-generation sequencing generating large amounts of genomic data, gene expression signatures are becoming critically important tools for the interpretation of these data, and are poised to have a substantial effect on diagnosis, management, and prognosis for a number of diseases. It is becoming crucial to establish whether the expression patterns and statistical properties of sets of genes, or gene signatures, are conserved across independent datasets. Conversely,...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/s41596-019-0136-8

Authors


More by this author
Institution:
University of Oxford
Department:
Oncology
Oxford college:
St Hugh's College
Role:
Author
ORCID:
0000-0002-5027-1277
More by this author
Institution:
University of Oxford
Department:
Oncology
Role:
Author
ORCID:
0000-0002-6718-855X
More by this author
Institution:
University of Oxford
Department:
Oncology
Role:
Author
More by this author
Institution:
University of Oxford
Department:
Oncology
Role:
Author
ORCID:
0000-0003-4390-8767
More by this author
Role:
Author
ORCID:
0000-0002-0839-3449
More from this funder
Name:
Cancer Research
Funding agency for:
Buffa, F
Grant:
772970
More from this funder
Name:
European Research Council
Funding agency for:
Buffa, F
Grant:
772970
More from this funder
Name:
Medical Research Council
Funding agency for:
Domingo, E
Maughan, T
Grant:
MR/M016587/1
MR/M016587/1
Publisher:
Springer Nature
Journal:
Nature Protocols More from this journal
Volume:
14
Pages:
1377–1400
Publication date:
2019-04-10
Acceptance date:
2019-01-11
DOI:
EISSN:
1750-2799
ISSN:
1754-2189
Pmid:
30971781
Language:
English
Pubs id:
pubs:987943
UUID:
uuid:897cb186-92b0-44e2-b94f-447c3a5a18bc
Local pid:
pubs:987943
Source identifiers:
987943
Deposit date:
2019-06-19

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