PuSH - Publication Server of Helmholtz Zentrum München

Buchka, S.* ; Hapfelmeier, A.* ; Gardner, P.P.* ; Wilson, R. ; Boulesteix, A.L.*

On the optimistic performance evaluation of newly introduced bioinformatic methods.

Genome Biol. 22:152 (2021)
Publ. Version/Full Text Research data DOI
Open Access Gold
Creative Commons Lizenzvertrag
Most research articles presenting new data analysis methods claim that "the new method performs better than existing methods," but the veracity of such statements is questionable. Our manuscript discusses and illustrates consequences of the optimistic bias occurring during the evaluation of novel data analysis methods, that is, all biases resulting from, for example, selection of datasets or competing methods, better ability to fix bugs in a preferred method, and selective reporting of method variants. We quantitatively investigate this bias using an example from epigenetic analysis: normalization methods for data generated by the Illumina HumanMethylation450K BeadChip microarray.
Altmetric
Additional Metrics?
Edit extra informations Login
Publication type Article: Journal article
Document type Scientific Article
Keywords Benchmarking ; Illumina Humanmethylation450k Beadchip ; Neutral Comparison Study ; Normalization ; Optimistic Bias
ISSN (print) / ISBN 1474-760X
e-ISSN 1465-6906
Journal Genome Biology
Quellenangaben Volume: 22, Issue: 1, Pages: , Article Number: 152 Supplement: ,
Publisher BioMed Central
Publishing Place Campus, 4 Crinan St, London N1 9xw, England
Reviewing status Peer reviewed
Grants Deutsche Forschungsgemeinschaft