TY - JOUR
T1 - Truncated rank correlation (TRC) as a robust measure of test-retest reliability in mass spectrometry data
AU - Lim, Johan
AU - Yu, Donghyeon
AU - Kuo, Hsun Chih
AU - Choi, Hyungwon
AU - Walmsley, Scott
N1 - Publisher Copyright:
© 2019 Walter de Gruyter GmbH, Berlin/Boston.
PY - 2019
Y1 - 2019
N2 - In mass spectrometry (MS) experiments, more than thousands of peaks are detected in the space of mass-to-charge ratio and chromatographic retention time, each associated with an abundance measurement. However, a large proportion of the peaks consists of experimental noise and low abundance compounds are typically masked by noise peaks, compromising the quality of the data. In this paper, we propose a new measure of similarity between a pair of MS experiments, called truncated rank correlation (TRC). To provide a robust metric of similarity in noisy high-dimensional data, TRC uses truncated top ranks (or top m-ranks) for calculating correlation. A comprehensive numerical study suggests that TRC outperforms traditional sample correlation and Kendall's τ. We apply TRC to measuring test-retest reliability of two MS experiments, including biological replicate analysis of the metabolome in HEK293 cells and metabolomic profiling of benign prostate hyperplasia (BPH) patients. An R package trc of the proposed TRC and related functions is available at https://sites.google.com/site/dhyeonyu/software.
AB - In mass spectrometry (MS) experiments, more than thousands of peaks are detected in the space of mass-to-charge ratio and chromatographic retention time, each associated with an abundance measurement. However, a large proportion of the peaks consists of experimental noise and low abundance compounds are typically masked by noise peaks, compromising the quality of the data. In this paper, we propose a new measure of similarity between a pair of MS experiments, called truncated rank correlation (TRC). To provide a robust metric of similarity in noisy high-dimensional data, TRC uses truncated top ranks (or top m-ranks) for calculating correlation. A comprehensive numerical study suggests that TRC outperforms traditional sample correlation and Kendall's τ. We apply TRC to measuring test-retest reliability of two MS experiments, including biological replicate analysis of the metabolome in HEK293 cells and metabolomic profiling of benign prostate hyperplasia (BPH) patients. An R package trc of the proposed TRC and related functions is available at https://sites.google.com/site/dhyeonyu/software.
KW - Kendall's τ
KW - mass spectrometry data
KW - test-retest reliability
KW - truncated rank
UR - http://www.scopus.com/inward/record.url?scp=85067189898&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85067189898&partnerID=8YFLogxK
U2 - 10.1515/sagmb-2018-0056
DO - 10.1515/sagmb-2018-0056
M3 - Article
C2 - 31145698
AN - SCOPUS:85067189898
SN - 1544-6115
VL - 18
JO - Statistical Applications in Genetics and Molecular Biology
JF - Statistical Applications in Genetics and Molecular Biology
IS - 4
M1 - 20180056
ER -