Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data.
Pakkir Shah AK, Walter A, Ottosson F, Russo F, Navarro-Diaz M, Boldt J, Kalinski JJ, Kontou EE, Elofson J, Polyzois A, González-Marín C, Farrell S, Aggerbeck MR, Pruksatrakul T, Chan N, Wang Y, Pöchhacker M, Brungs C, Cámara B, Caraballo-Rodríguez AM, Cumsille A, de Oliveira F, Dührkop K, El Abiead Y, Geibel C, Graves LG, Hansen M, Heuckeroth S, Knoblauch S, Kostenko A, Kuijpers MCM, Mildau K, Papadopoulos Lambidis S, Portal Gomes PW, Schramm T, Steuer-Lodd K, Stincone P, Tayyab S, Vitale GA, Wagner BC, Xing S, Yazzie MT, Zuffa S, de Kruijff M, Beemelmanns C, Link H, Mayer C, van der Hooft JJJ, Damiani T, Pluskal T, Dorrestein P, Stanstrup J, Schmid R, Wang M, Aron A, Ernst M, Petras D.
Pakkir Shah AK, et al.
Nat Protoc. 2025 Jan;20(1):92-162. doi: 10.1038/s41596-024-01046-3. Epub 2024 Sep 20.
Nat Protoc. 2025.
PMID: 39304763
We provide explanations and code in two scripting languages (R and Python) as well as the QIIME2 framework for all protocol steps, from data clean-up to statistical analysis. ...
We provide explanations and code in two scripting languages (R and Python) as well as the QIIME2 framework for all protocol steps, fr …