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. 2021 Oct 14;4:1190. doi: 10.1038/s42003-021-02726-6

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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 — The deep representation models trained on the RSMs with eight different compositions as well as DIA-NN were tested on the S1-1 run of mouse cerebellum dataset using a DIA-Umpire library and b DDA master sample library. Two-species FDR estimation method was used as in Fig. 2. The numbers of mouse precursors identified at different FDRs were plotted. r, the basic resolution that can be specified by users according to the acquisition resolution.