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. 2021 Nov 25;11:22916. doi: 10.1038/s41598-021-02343-7

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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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

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MDS plot of 151 datasets utilized for ML classification. Clustering was performed with Euclidian distances across the top 500 genes based on log2 standard deviation. Datasets are demarked by color, representing the tissue site of sampling. Labels 1, 2, and 3 demark distinct gene expression clusters across tissue types, regardless of etiological component, based on expressional variation. Label 1 consists of healthy (non-consolidated) and diseased (consolidated) lung tissue. Label 2 consists of lymphoid tissue from Tizioto and colleagues³⁰ and Behura and colleagues³¹. Label 3 consists of lymphoid (bronchial) tissue from Johnston and colleagues³².