DIAMetAlyzer allows automated false-discovery rate-controlled analysis for data-independent acquisition in metabolomics

The extraction of meaningful biological knowledge from high-throughput mass spectrometry data relies on limiting false discoveries to a manageable amount. For targeted approaches in metabolomics a main challenge is the detection of false positive metabolic features in the low signal-to-noise ranges...

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Detalles Bibliográficos
Autores principales: Alka, Oliver, Shanthamoorthy, Premy, Witting, Michael, Kleigrewe, Karin, Kohlbacher, Oliver, Röst, Hannes L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8924252/
https://www.ncbi.nlm.nih.gov/pubmed/35292629
http://dx.doi.org/10.1038/s41467-022-29006-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8924252/
https://www.ncbi.nlm.nih.gov/pubmed/35292629
http://dx.doi.org/10.1038/s41467-022-29006-z

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