Standard
A proteomics sample metadata representation for multiomics integration and big data analysis. / Dai, Chengxin; Füllgrabe, Anja; Pfeuffer, Julianus; Solovyeva, Elizaveta M.; Deng, Jingwen; Moreno, Pablo; Kamatchinathan, Selvakumar; Kundu, Deepti Jaiswal; George, Nancy; Fexova, Silvie; Grüning, Björn; Föll, Melanie Christine; Griss, Johannes; Vaudel, Marc; Audain, Enrique; Locard-Paulet, Marie; Turewicz, Michael; Eisenacher, Martin; Uszkoreit, Julian; Van Den Bossche, Tim; Schwämmle, Veit; Webel, Henry; Schulze, Stefan; Bouyssié, David; Jayaram, Savita; Duggineni, Vinay Kumar; Samaras, Patroklos; Wilhelm, Mathias; Choi, Meena; Wang, Mingxun; Kohlbacher, Oliver; Brazma, Alvis; Papatheodorou, Irene; Bandeira, Nuno; Deutsch, Eric W.; Vizcaíno, Juan Antonio; Bai, Mingze; Sachsenberg, Timo; Levitsky, Lev I.; Perez-Riverol, Yasset.
In:
Nature Communications, Vol. 12, No. 1, 5854, 2021.
Research output: Contribution to journal › Journal article › Research › peer-review
Harvard
Dai, C, Füllgrabe, A, Pfeuffer, J, Solovyeva, EM, Deng, J, Moreno, P, Kamatchinathan, S, Kundu, DJ, George, N, Fexova, S, Grüning, B, Föll, MC, Griss, J, Vaudel, M, Audain, E
, Locard-Paulet, M, Turewicz, M, Eisenacher, M, Uszkoreit, J, Van Den Bossche, T, Schwämmle, V
, Webel, H, Schulze, S, Bouyssié, D, Jayaram, S, Duggineni, VK, Samaras, P, Wilhelm, M, Choi, M, Wang, M, Kohlbacher, O, Brazma, A, Papatheodorou, I, Bandeira, N, Deutsch, EW, Vizcaíno, JA, Bai, M, Sachsenberg, T, Levitsky, LI & Perez-Riverol, Y 2021, '
A proteomics sample metadata representation for multiomics integration and big data analysis',
Nature Communications, vol. 12, no. 1, 5854.
https://doi.org/10.1038/s41467-021-26111-3APA
Dai, C., Füllgrabe, A., Pfeuffer, J., Solovyeva, E. M., Deng, J., Moreno, P., Kamatchinathan, S., Kundu, D. J., George, N., Fexova, S., Grüning, B., Föll, M. C., Griss, J., Vaudel, M., Audain, E.
, Locard-Paulet, M., Turewicz, M., Eisenacher, M., Uszkoreit, J., ... Perez-Riverol, Y. (2021).
A proteomics sample metadata representation for multiomics integration and big data analysis.
Nature Communications,
12(1), [5854].
https://doi.org/10.1038/s41467-021-26111-3Vancouver
Dai C, Füllgrabe A, Pfeuffer J, Solovyeva EM, Deng J, Moreno P et al.
A proteomics sample metadata representation for multiomics integration and big data analysis.
Nature Communications. 2021;12(1). 5854.
https://doi.org/10.1038/s41467-021-26111-3Author
Dai, Chengxin ; Füllgrabe, Anja ; Pfeuffer, Julianus ; Solovyeva, Elizaveta M. ; Deng, Jingwen ; Moreno, Pablo ; Kamatchinathan, Selvakumar ; Kundu, Deepti Jaiswal ; George, Nancy ; Fexova, Silvie ; Grüning, Björn ; Föll, Melanie Christine ; Griss, Johannes ; Vaudel, Marc ; Audain, Enrique ; Locard-Paulet, Marie ; Turewicz, Michael ; Eisenacher, Martin ; Uszkoreit, Julian ; Van Den Bossche, Tim ; Schwämmle, Veit ; Webel, Henry ; Schulze, Stefan ; Bouyssié, David ; Jayaram, Savita ; Duggineni, Vinay Kumar ; Samaras, Patroklos ; Wilhelm, Mathias ; Choi, Meena ; Wang, Mingxun ; Kohlbacher, Oliver ; Brazma, Alvis ; Papatheodorou, Irene ; Bandeira, Nuno ; Deutsch, Eric W. ; Vizcaíno, Juan Antonio ; Bai, Mingze ; Sachsenberg, Timo ; Levitsky, Lev I. ; Perez-Riverol, Yasset. / A proteomics sample metadata representation for multiomics integration and big data analysis. In: Nature Communications. 2021 ; Vol. 12, No. 1.
Bibtex
@article{931fc60a6878432a88af8464def185f3,
title = "A proteomics sample metadata representation for multiomics integration and big data analysis",
abstract = "The amount of public proteomics data is rapidly increasing but there is no standardized format to describe the sample metadata and their relationship with the dataset files in a way that fully supports their understanding or reanalysis. Here we propose to develop the transcriptomics data format MAGE-TAB into a standard representation for proteomics sample metadata. We implement MAGE-TAB-Proteomics in a crowdsourcing project to manually curate over 200 public datasets. We also describe tools and libraries to validate and submit sample metadata-related information to the PRIDE repository. We expect that these developments will improve the reproducibility and facilitate the reanalysis and integration of public proteomics datasets.",
author = "Chengxin Dai and Anja F{\"u}llgrabe and Julianus Pfeuffer and Solovyeva, {Elizaveta M.} and Jingwen Deng and Pablo Moreno and Selvakumar Kamatchinathan and Kundu, {Deepti Jaiswal} and Nancy George and Silvie Fexova and Bj{\"o}rn Gr{\"u}ning and F{\"o}ll, {Melanie Christine} and Johannes Griss and Marc Vaudel and Enrique Audain and Marie Locard-Paulet and Michael Turewicz and Martin Eisenacher and Julian Uszkoreit and {Van Den Bossche}, Tim and Veit Schw{\"a}mmle and Henry Webel and Stefan Schulze and David Bouyssi{\'e} and Savita Jayaram and Duggineni, {Vinay Kumar} and Patroklos Samaras and Mathias Wilhelm and Meena Choi and Mingxun Wang and Oliver Kohlbacher and Alvis Brazma and Irene Papatheodorou and Nuno Bandeira and Deutsch, {Eric W.} and Vizca{\'i}no, {Juan Antonio} and Mingze Bai and Timo Sachsenberg and Levitsky, {Lev I.} and Yasset Perez-Riverol",
note = "Publisher Copyright: {\textcopyright} 2021, The Author(s).",
year = "2021",
doi = "10.1038/s41467-021-26111-3",
language = "English",
volume = "12",
journal = "Nature Communications",
issn = "2041-1723",
publisher = "nature publishing group",
number = "1",
}
RIS
TY - JOUR
T1 - A proteomics sample metadata representation for multiomics integration and big data analysis
AU - Dai, Chengxin
AU - Füllgrabe, Anja
AU - Pfeuffer, Julianus
AU - Solovyeva, Elizaveta M.
AU - Deng, Jingwen
AU - Moreno, Pablo
AU - Kamatchinathan, Selvakumar
AU - Kundu, Deepti Jaiswal
AU - George, Nancy
AU - Fexova, Silvie
AU - Grüning, Björn
AU - Föll, Melanie Christine
AU - Griss, Johannes
AU - Vaudel, Marc
AU - Audain, Enrique
AU - Locard-Paulet, Marie
AU - Turewicz, Michael
AU - Eisenacher, Martin
AU - Uszkoreit, Julian
AU - Van Den Bossche, Tim
AU - Schwämmle, Veit
AU - Webel, Henry
AU - Schulze, Stefan
AU - Bouyssié, David
AU - Jayaram, Savita
AU - Duggineni, Vinay Kumar
AU - Samaras, Patroklos
AU - Wilhelm, Mathias
AU - Choi, Meena
AU - Wang, Mingxun
AU - Kohlbacher, Oliver
AU - Brazma, Alvis
AU - Papatheodorou, Irene
AU - Bandeira, Nuno
AU - Deutsch, Eric W.
AU - Vizcaíno, Juan Antonio
AU - Bai, Mingze
AU - Sachsenberg, Timo
AU - Levitsky, Lev I.
AU - Perez-Riverol, Yasset
N1 - Publisher Copyright:
© 2021, The Author(s).
PY - 2021
Y1 - 2021
N2 - The amount of public proteomics data is rapidly increasing but there is no standardized format to describe the sample metadata and their relationship with the dataset files in a way that fully supports their understanding or reanalysis. Here we propose to develop the transcriptomics data format MAGE-TAB into a standard representation for proteomics sample metadata. We implement MAGE-TAB-Proteomics in a crowdsourcing project to manually curate over 200 public datasets. We also describe tools and libraries to validate and submit sample metadata-related information to the PRIDE repository. We expect that these developments will improve the reproducibility and facilitate the reanalysis and integration of public proteomics datasets.
AB - The amount of public proteomics data is rapidly increasing but there is no standardized format to describe the sample metadata and their relationship with the dataset files in a way that fully supports their understanding or reanalysis. Here we propose to develop the transcriptomics data format MAGE-TAB into a standard representation for proteomics sample metadata. We implement MAGE-TAB-Proteomics in a crowdsourcing project to manually curate over 200 public datasets. We also describe tools and libraries to validate and submit sample metadata-related information to the PRIDE repository. We expect that these developments will improve the reproducibility and facilitate the reanalysis and integration of public proteomics datasets.
U2 - 10.1038/s41467-021-26111-3
DO - 10.1038/s41467-021-26111-3
M3 - Journal article
C2 - 34615866
AN - SCOPUS:85116400934
VL - 12
JO - Nature Communications
JF - Nature Communications
SN - 2041-1723
IS - 1
M1 - 5854
ER -
