Prediction errors in learning drug response from gene expression data : influence of labeling, sample size, and machine learning algorithm

Bayer, Immanuel; Groth, Philip; Schneckener, Sebastian

Prediction errors in learning drug response from gene expression data : influence of labeling, sample size, and machine learning algorithm

Dateien

Bayer_264785.pdfGröße: 1.28 MBDownloads: 454

Datum

2013

Autor:innen

Bayer, Immanuel

Groth, Philip

Schneckener, Sebastian

Open Access-Veröffentlichung

Open Access Gold

Sammlungen

Informatik und Informationswissenschaft

Publikationstyp

Zeitschriftenartikel

Publikationsstatus

Published

Erschienen in

PLoS ONE. 2013, 8(7), pp. e70294. eISSN 1932-6203. Available under: doi: 10.1371/journal.pone.0070294

Zusammenfassung

Model-based prediction is dependent on many choices ranging from the sample collection and prediction endpoint to the choice of algorithm and its parameters. Here we studied the effects of such choices, exemplified by predicting sensitivity (as IC50) of cancer cell lines towards a variety of compounds. For this, we used three independent sample collections and applied several machine learning algorithms for predicting a variety of endpoints for drug response. We compared all possible models for combinations of sample collections, algorithm, drug, and labeling to an identically generated null model. The predictability of treatment effects varies among compounds, i.e. response could be predicted for some but not for all. The choice of sample collection plays a major role towards lowering the prediction error, as does sample size. However, we found that no algorithm was able to consistently outperform the other and there was no significant difference between regression and two- or three class predictors in this experimental setting. These results indicate that response-modeling projects should direct efforts mainly towards sample collection and data quality, rather than method adjustment.

Fachgebiet (DDC)

004 Informatik

Zitieren

ISO 690

BAYER, Immanuel, Philip GROTH, Sebastian SCHNECKENER, 2013. Prediction errors in learning drug response from gene expression data : influence of labeling, sample size, and machine learning algorithm. In: PLoS ONE. 2013, 8(7), pp. e70294. eISSN 1932-6203. Available under: doi: 10.1371/journal.pone.0070294

BibTex

@article{Bayer2013Predi-26478,
  year={2013},
  doi={10.1371/journal.pone.0070294},
  title={Prediction errors in learning drug response from gene expression data : influence of labeling, sample size, and machine learning algorithm},
  number={7},
  volume={8},
  journal={PLoS ONE},
  author={Bayer, Immanuel and Groth, Philip and Schneckener, Sebastian},
  note={Article Number: e70294}
}

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Universitätsbibliographie

Ja