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. 2018 Aug 1;8:11568. doi: 10.1038/s41598-018-29969-4

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© The Author(s) 2018

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Correlation of transcriptional expression measured by microarray versus qPCR. 17% (36 genes) of the 212 novel parasite biomarkers of transmission stage malaria identified by microarray was subjected to validation by qPCR using primers specific for the gene of interest and RNA template isolated from infected mosquitoes. Each dot represents an individual gene in the microarray dataset. Correlation between fold change by microarray (x axis) versus copy number ± standard error by qPCR (y axis) increases as the parasite developmentally progresses through the mosquito. Correlation was calculated using the Spearman’s ρ nonparametric test. Error bars indicate standard deviation for qPCR.