Faster cyclic loess: Normalizing RNA arrays via linear models

Karla V. Ballman; Diane E. Grill; Ann L. Oberg; Terry M. Therneau

doi:10.1093/bioinformatics/bth327

Faster cyclic loess: Normalizing RNA arrays via linear models

Karla V. Ballman, Diane E. Grill, Ann L. Oberg, Terry M. Therneau

Quantitative Health Sciences

Research output: Contribution to journal › Article › peer-review

134 Scopus citations

Abstract

Motivation: Our goal was to develop a normalization technique that yields results similar to cyclic loess normalization and with speed comparable to quantile normalization. Results: Fastlo yields normalized values similar to cyclic loess and quantile normalization and is fast; it is at least an order of magnitude faster than cyclic loess and approaches the speed of quantile normalization. Furthermore, fastlo is more versatile than both cyclic loess and quantile normalization because it is model-based.

Original language	English (US)
Pages (from-to)	2778-2786
Number of pages	9
Journal	Bioinformatics
Volume	20
Issue number	16
DOIs	https://doi.org/10.1093/bioinformatics/bth327
State	Published - Nov 1 2004

ASJC Scopus subject areas

Statistics and Probability
Biochemistry
Molecular Biology
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics

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10.1093/bioinformatics/bth327

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AU - Oberg, Ann L.

AU - Therneau, Terry M.

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Faster cyclic loess: Normalizing RNA arrays via linear models

Abstract

ASJC Scopus subject areas

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