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. 2018 Oct 9;8:15039. doi: 10.1038/s41598-018-33280-7

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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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Performance of the ELV-SWATH-MS workflow. (a) Quantitative data of 888 proteins in ELVs, MVs and UP samples (3 replicates for each sample) were demonstrated in a heat map manner. The scale of SWATH-estimated protein intensity showed the relative amount of original data after Total Area Sum (TAS) normalization. The missing values (6 out of 7,992 data across all replicates) were labeled in black color. (b) Numbers of unique peptide per protein. (c) Pearson correlation of nine sample replicates based on 888 expression data. Each number in the sample matrix was the correlation coefficient (r), in which r = 1 was a perfect positive relationship, and r = 0 showed no association between a sample pair. (d) The coefficient of variation (CV) of 888 protein quantitation in urinary ELVs, in which the median-CV was 7.7%.