Imperial College London
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ProfessorAnneO'Garra

Faculty of Medicine, National Heart & Lung Institute

Chair in Infection Immunology
 
 
 
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a.ogarra

 
 
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Location

 

Norfolk PlaceSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Altmann:2021:10.1038/s41467-021-24584-w,
author = {Altmann, MC and Rinchai, D and Baldwin, N and Toufiq, M and Whalen, E and Garand, M and Kabeer, BSA and Alfaki, M and Presnell, S and Khaenam, P and Benitez, AA and Mougin, F and Thébault, P and Chiche, L and Jourde-Chiche, N and Phillips, JT and Klintmalm, G and O'Garra, A and Berry, M and Bloom, C and Wilkinson, RJ and Graham, CM and Lipman, M and Lertmemongkolchai, G and Bedognetti, D and Thiebaut, R and Kheradmand, F and Mejias, A and Ramilo, O and Palucka, K and Pascual, V and Banchereau, J and Chaussabel, D},
doi = {10.1038/s41467-021-24584-w},
journal = {Nature Communications},
pages = {1--19},
title = {Development of a fixed module repertoire for the analysis and interpretation of blood transcriptome data},
url = {http://dx.doi.org/10.1038/s41467-021-24584-w},
volume = {12},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - As the capacity for generating large-scale molecular profiling data continues to grow, the ability to extract meaningful biological knowledge from it remains a limitation. Here, we describe the development of a new fixed repertoire of transcriptional modules, BloodGen3, that is designed to serve as a stable reusable framework for the analysis and interpretation of blood transcriptome data. The construction of this repertoire is based on co-clustering patterns observed across sixteen immunological and physiological states encompassing 985 blood transcriptome profiles. Interpretation is supported by customized resources, including module-level analysis workflows, fingerprint grid plot visualizations, interactive web applications and an extensive annotation framework comprising functional profiling reports and reference transcriptional profiles. Taken together, this well-characterized and well-supported transcriptional module repertoire can be employed for the interpretation and benchmarking of blood transcriptome profiles within and across patient cohorts. Blood transcriptome fingerprints for the 16 reference cohorts can be accessed interactively via: https://drinchai.shinyapps.io/BloodGen3Module/.
AU  - Altmann,MC
AU  - Rinchai,D
AU  - Baldwin,N
AU  - Toufiq,M
AU  - Whalen,E
AU  - Garand,M
AU  - Kabeer,BSA
AU  - Alfaki,M
AU  - Presnell,S
AU  - Khaenam,P
AU  - Benitez,AA
AU  - Mougin,F
AU  - Thébault,P
AU  - Chiche,L
AU  - Jourde-Chiche,N
AU  - Phillips,JT
AU  - Klintmalm,G
AU  - O'Garra,A
AU  - Berry,M
AU  - Bloom,C
AU  - Wilkinson,RJ
AU  - Graham,CM
AU  - Lipman,M
AU  - Lertmemongkolchai,G
AU  - Bedognetti,D
AU  - Thiebaut,R
AU  - Kheradmand,F
AU  - Mejias,A
AU  - Ramilo,O
AU  - Palucka,K
AU  - Pascual,V
AU  - Banchereau,J
AU  - Chaussabel,D
DO  - 10.1038/s41467-021-24584-w
EP  - 19
PY  - 2021///
SN  - 2041-1723
SP  - 1
TI  - Development of a fixed module repertoire for the analysis and interpretation of blood transcriptome data
T2  - Nature Communications
UR  - http://dx.doi.org/10.1038/s41467-021-24584-w
UR  - https://www.nature.com/articles/s41467-021-24584-w
UR  - http://hdl.handle.net/10044/1/90762
VL  - 12
ER  -
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