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. 2021 May 28;12:3241. doi: 10.1038/s41467-021-23461-w

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© The Author(s) 2021

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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Fig. 4 — a Diagrammatic representation of the sagittal plane of the bovine lens detailing the 4 major anatomical regions. b HIT-MAP spatial k-means clustering of a MALDI–MSI lens dataset based on specification of between k = 1 − 16 data-driven segments (colours show individual segments). Note the unbiased annular segmentation in line with lens anatomy. c The median mass variance in exact mass-filtering of candidate peptides against m/z features within the experimental mass spectrum, and the subsequent median peptide score of m/z features shows improved peptide scoring and declining ppm error during exact mass filtering with increased segmentation. d The total number of non-redundant peptide and protein identifications by HIT-MAP with varying segmentation of the lens, and e the total number of non-redundant protein identifications by HIT-MAP with varying segmentation of the lens—protein IDs are grouped and coloured by their identification frequency across the serial segmentation test.