The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Assessment of Variability in the SOMAscan Assay
Open accessAbstract
SOMAscan is an aptamer-based proteomics assay capable of measuring 1,305 human protein analytes in serum, plasma, and other biological matrices with high sensitivity and specificity. In this work, we present a comprehensive meta-analysis of performance based on multiple serum and plasma runs using the current 1.3 k assay, as well as the previous 1.1 k version. We discuss normalization procedures and examine different strategies to minimize intra- and interplate nuisance effects. We implement a meta-analysis based on calibrator samples to characterize the coefficient of variation and signal-over-background intensity of each protein analyte. By incorporating coefficient of variation estimates into a theoretical model of statistical variability, we also provide a framework to enable rigorous statistical tests of significance in intervention studies and clinical trials, as well as quality control within and across laboratories. Furthermore, we investigate the stability of healthy subject baselines and determine the set of analytes that exhibit biologically stable baselines after technical variability is factored in. This work is accompanied by an interactive web-based tool, an initiative with the potential to become the cornerstone of a regularly updated, high quality repository with data sharing, reproducibility, and reusability as ultimate goals.
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Cites
Signalling pathways of the TNF superfamily: a double-edged sword
Aggarwal, B. B. (2003) · Nature Reviews Immunology · doi:10.1038/nri1184 · Cited by 2,793
Aptamer-Based Multiplexed Proteomic Technology for Biomarker Discovery
Gold, L., Ayers, D., Bertino, J., Bock, C., Bock, A., Brody, E. N., Carter, J., Dalby, A. B., Eaton, B. E., Fitzwater, T., et al. (2010) · PLoS ONE · doi:10.1371/journal.pone.0015004 · Cited by 1,754
Loffredo, F. S., Steinhauser, M. L., Jay, S. M., Gannon, J., Pancoast, J. R., Yalamanchi, P., Sinha, M., Dall’Osso, C., Khong, D., Shadrach, J. L., et al. (2013) · Cell · doi:10.1016/j.cell.2013.04.015 · Cited by 948
A Modular Analysis Framework for Blood Genomics Studies: Application to Systemic Lupus Erythematosus
Chaussabel, D., Quinn, C., Shen, J., Patel, P., Glaser, C., Baldwin, N., Stichweh, D., Blankenship, D., Li, L., Munagala, I., et al. (2008) · Immunity · doi:10.1016/j.immuni.2008.05.012 · Cited by 649
Batch effect removal methods for microarray gene expression data integration: a survey
Lazar, C., Meganck, S., Taminau, J., Steenhoff, D., Coletta, A., Molter, C., Weiss-Solis, D. Y., Duque, R., Bersini, H., & Nowe, A. (2013) · Briefings in Bioinformatics · doi:10.1093/bib/bbs037 · Cited by 333
Alzheimer's disease biomarker discovery using SOMAscan multiplexed protein technology
Sattlecker, M., Kiddle, S. J., Newhouse, S., Proitsi, P., Nelson, S., Williams, S., Johnston, C., Killick, R., Simmons, A., Westman, E., et al. (2014) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2013.09.016 · Cited by 223 · cited 3×
“(6) using the median, 75th and 90th percentiles of the intraplate CV of calibrators are compared to the measured fold-change frequency distributions of intraplate pairs of replicates among QC_SOMAscan and QC_CHI quality control samples.”
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Cited by
Co-regulatory networks of human serum proteins link genetics to disease
Emilsson, V., Ilkov, M., Lamb, J. R., Finkel, N., Gudmundsson, E. F., Pitts, R., Hoover, H., Gudmundsdottir, V., Horman, S. R., Aspelund, T., et al. (2018) · Science · doi:10.1126/science.aaq1327 · Cited by 680
Large-scale plasma proteomics comparisons through genetics and disease associations
Eldjarn, G. H., Ferkingstad, E., Lund, S. H., Helgason, H., Magnusson, O. T., Gunnarsdottir, K., Olafsdottir, T. A., Halldorsson, B. V., Olason, P. I., Zink, F., et al. (2023) · Nature · doi:10.1038/s41586-023-06563-x · Cited by 583
Plasma proteomic signature of age in healthy humans
Tanaka, T., Biancotto, A., Moaddel, R., Moore, A. Z., Gonzalez‐Freire, M., Aon, M. A., Candia, J., Zhang, P., Cheung, F., Fantoni, G., et al. (2018) · Aging Cell · doi:10.1111/acel.12799 · Cited by 562
Self-citationPlasma protein patterns as comprehensive indicators of health
Williams, S. A., Kivimaki, M., Langenberg, C., Hingorani, A. D., Casas, J. P., Bouchard, C., Jonasson, C., Sarzynski, M. A., Shipley, M. J., Alexander, L., et al. (2019) · Nature Medicine · doi:10.1038/s41591-019-0665-2 · Cited by 506
Effects of microbiota-directed foods in gnotobiotic animals and undernourished children
Gehrig, J. L., Venkatesh, S., Chang, H.-W., Hibberd, M. C., Kung, V. L., Cheng, J., Chen, R. Y., Subramanian, S., Cowardin, C. A., Meier, M. F., et al. (2019) · Science · doi:10.1126/science.aau4732 · Cited by 431
Metadata
- Authors
- Candia, J., Cheung, F., Kotliarov, Y., Fantoni, G., Sellers, B., Griesman, T., Huang, J., Stuccio, S., Zingone, A., Ryan, B. M., Tsang, J. S., & Biancotto, A.
- Venue
- Scientific Reports
- Published
- 2017-10-27
- Volume
- 7
- Issue
- 1
- Pages
- 14248-14248
- ISSN
- 2045-2322 (ISSN-L)
- OpenAlex
- W2767195935
- Cited by
- 393
- References
- 6
- FWCI
- 7.57
- Type
- journal article
- Language
- en
- Open access
- gold
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- Candia, J., Cheung, F., Kotliarov, Y., Fantoni, G., Sellers, B., Griesman, T., Huang, J., Stuccio, S., Zingone, A., Ryan, B. M., Tsang, J. S., & Biancotto, A. (2017). Assessment of Variability in the SOMAscan Assay. Scientific Reports. https://doi.org/10.1038/s41598-017-14755-5
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