glioma: Glioma Metabolomics
In SLOPE: Sorted L1 Penalized Estimation
glioma R Documentation
Glioma Metabolomics
Description
Metabolomics dataset from 165 different plasma measurements from
94 patients (cases) with glioma (brain tumours) and 71 healthy controls. The
goal is to predict whether a sample is from a patient or a control based
on the metabolite measurements.
Usage
glioma
Format
165 observations from 138 variables represented as a list consisting
of a binary response (factor) vector y with levels 'control' and 'case'
indicating whether the sample is from a healthy control or a patient with
glioma, as well as x: a matrix of 138 metabolite measurements.
Preprocessing
We have removed the patients with meningioma from the original dataset (which
contained 235 samples) to create a binary classification problem. Also,
the authors originally had 188 features but removed some of these due to
missing data.
Source
Godlewski, A., Czajkowski, M., Mojsak, P., Pienkowski, T., Gosk, W.,
Lyson, T., Mariak, Z., Reszec, J., Kondraciuk, M., Kaminski, K., Kretowski,
M., Moniuszko, M., Kretowski, A., & Ciborowski, M. (2023). A comparison of
different machine-learning techniques for the selection of a panel of
metabolites allowing early detection of brain tumors. Scientific Reports,
13(1), 11044. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1038/s41598-023-38243-1")}
SLOPE documentation built on Jan. 28, 2026, 9:07 a.m.
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| glioma | R Documentation |
Glioma Metabolomics
Description
Metabolomics dataset from 165 different plasma measurements from 94 patients (cases) with glioma (brain tumours) and 71 healthy controls. The goal is to predict whether a sample is from a patient or a control based on the metabolite measurements.
Usage
glioma
Format
165 observations from 138 variables represented as a list consisting
of a binary response (factor) vector y with levels 'control' and 'case'
indicating whether the sample is from a healthy control or a patient with
glioma, as well as x: a matrix of 138 metabolite measurements.
Preprocessing
We have removed the patients with meningioma from the original dataset (which contained 235 samples) to create a binary classification problem. Also, the authors originally had 188 features but removed some of these due to missing data.
Source
Godlewski, A., Czajkowski, M., Mojsak, P., Pienkowski, T., Gosk, W., Lyson, T., Mariak, Z., Reszec, J., Kondraciuk, M., Kaminski, K., Kretowski, M., Moniuszko, M., Kretowski, A., & Ciborowski, M. (2023). A comparison of different machine-learning techniques for the selection of a panel of metabolites allowing early detection of brain tumors. Scientific Reports, 13(1), 11044. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1038/s41598-023-38243-1")}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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