Partial least squares

Comparison of dimensionality reduction methods to predict genomic breeding values for carcass traits in pigs

C. F. Azevedo, Nascimento, M., Silva, F. F., Resende, M. D. V., Lopes, P. S., Guimarães, S. E. F., and Glória, L. S., Comparison of dimensionality reduction methods to predict genomic breeding values for carcass traits in pigs, vol. 14, pp. 12217-12227, 2015.

A significant contribution of molecular genetics is the direct use of DNA information to identify genetically superior individuals. With this approach, genome-wide selection (GWS) can be used for this purpose. GWS consists of analyzing a large number of single nucleotide polymorphism markers widely distributed in the genome; however, because the number of markers is much larger than the number of genotyped individuals, and such markers are highly correlated, special statistical methods are widely required.

Partial least squares-based gene expression analysis in preeclampsia

F. Jiang, Yang, Y., Li, J., Li, W., Luo, Y., Li, Y., Zhao, H., Wang, X., Yin, G., and Wu, G., Partial least squares-based gene expression analysis in preeclampsia, vol. 14, pp. 6598-6604, 2015.

Preeclampsia is major cause of maternal and fetal morbidity and mortality. Currently, the etiology of preeclampsia is unclear. In this study, we investigated differences in gene expression between preeclampsia patients and controls using partial least squares-based analysis, which is more suitable than routine analysis. Expression profile data were downloaded from the Gene Expression Omnibus database. A total of 503 genes were found to be differentially expressed, including 248 downregulated genes and 255 overexpressed genes.

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