Branca, R. M. M. et al. HiRIEF LC–MS enables deep proteome coverage and unbiased proteogenomics. Nat. Methods 11, 59–62 (2014).

Article  CAS  PubMed  Google Scholar 

Wilhelm, M. et al. Mass-spectrometry-based draft of the human proteome. Nature 509, 582–587 (2014).

Article  CAS  PubMed  Google Scholar 

Kim, M. S. et al. A draft map of the human proteome. Nature 509, 575–581 (2014).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Aebersold, R. & Mann, M. Mass-spectrometric exploration of proteome structure and function. Nature 537, 347–355 (2016).

Article  CAS  PubMed  Google Scholar 

Bruderer, R. et al. Extending the limits of quantitative proteome profiling with data-independent acquisition and application to acetaminophen-treated three-dimensional liver microtissues. Mol. Cell. Proteomics 14, 1400–1410 (2015).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Demichev, V., Messner, C. B., Vernardis, S. I., Lilley, K. S. & Ralser, M. DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput. Nat. Methods 17, 41–44 (2020).

Article  CAS  PubMed  Google Scholar 

Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372 (2008).

Article  CAS  PubMed  Google Scholar 

Tyanova, S., Temu, T. & Cox, J. The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nat. Protoc. 11, 2301–2319 (2016).

Article  CAS  PubMed  Google Scholar 

Orsburn, B. C. Proteome Discoverer—a community enhanced data processing suite for protein informatics. Proteomes 9, 15 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Santos, M. D. M. et al. Simple, efficient and thorough shotgun proteomic analysis with PatternLab V. Nat. Protoc. 17, 1553–1578 (2022).

Article  CAS  PubMed  Google Scholar 

Röst, H. L. et al. OpenMS: a flexible open-source software platform for mass spectrometry data analysis. Nat. Methods 13, 741–748 (2016).

Article  PubMed  Google Scholar 

Cox, J. et al. Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Mol. Cell. Proteomics 13, 2513–2526 (2014).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Fischer, M. & Renard, B. Y. iPQF: a new peptide-to-protein summarization method using peptide spectra characteristics to improve protein quantification. Bioinformatics 32, 1040–1047 (2016).

Article  CAS  PubMed  Google Scholar 

The, M. & Käll, L. Integrated identification and quantification error probabilities for shotgun proteomics. Mol. Cell. Proteomics 18, 561–570 (2019).

Article  CAS  PubMed  Google Scholar 

Hultin-Rosenberg, L., Forshed, J., Branca, R. M. M., Lehtiö, J. & Johansson, H. J. Defining, comparing, and improving iTRAQ quantification in mass spectrometry proteomics data. Mol. Cell. Proteomics 12, 2021–2031 (2013).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kammers, K., Cole, R. N., Tiengwe, C. & Ruczinski, I. Detecting significant changes in protein abundance. EuPA Open Proteom. 7, 11–19 (2015).

Article  CAS  PubMed  PubMed Central  Google Scholar 

D’Angelo, G. et al. Statistical models for the analysis of isobaric tags multiplexed quantitative proteomics. J. Proteome Res. 16, 3124–3136 (2017).

Article  PubMed  Google Scholar 

Sartor, M. A. et al. Intensity-based hierarchical Bayes method improves testing for differentially expressed genes in microarray experiments. BMC Bioinform. 7, 538 (2006).

Article  Google Scholar 

Law, C. W., Chen, Y., Shi, W. & Smyth, G. K. voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol. 15, R29 (2014).

Article  PubMed  PubMed Central  Google Scholar 

Zhu, Y. et al. DEqMS: a method for accurate variance estimation in differential protein expression analysis. Mol. Cell. Proteomics 19, 1047–1057 (2020).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Smyth, G. K. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat. Appl. Genet. Mol. Biol. 3, 3 (2004).

Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).

Article  PubMed  PubMed Central  Google Scholar 

Zhou Tran, Y. et al. Immediate adaptation analysis implicates BCL6 as an EGFR-TKI combination therapy target in NSCLC. Mol. Cell. Proteomics 19, 928–943 (2020).

Article  PubMed  PubMed Central  Google Scholar 

Lehtiö, J. et al. Proteogenomics of non-small cell lung cancer reveals molecular subtypes associated with specific therapeutic targets and immune evasion mechanisms. Nat Cancer 2, 1224–1242 (2021).

Article  PubMed  PubMed Central  Google Scholar 

Topham, J. T. et al. Integrative analysis of KRAS wildtype metastatic pancreatic ductal adenocarcinoma reveals mutation and expression-based similarities to cholangiocarcinoma. Nat. Commun. 13, 5941 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Leo, I. R. et al. Integrative multi-omics and drug response profiling of childhood acute lymphoblastic leukemia cell lines. Nat. Commun. 13, 1691 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Hisaoka, M. et al. Preferential translation of p53 target genes. RNA Biol. 19, 437–452 (2022).

Article  CAS  PubMed  Google Scholar 

Nilsson, A. K. et al. The proteome signature of cord blood plasma with high hematopoietic stem and progenitor cell count. Stem Cell Res. 61, 102752 (2022).

Article  CAS  PubMed  Google Scholar 

Kang, J. Y. et al. LLPS of FXR1 drives spermiogenesis by activating translation of stored mRNAs. Science 377, eabj6647 (2022).

Article  CAS  PubMed  Google Scholar 

Jansson, M. D. et al. Regulation of translation by site-specific ribosomal RNA methylation. Nat. Struct. Mol. Biol. 28, 889–899 (2021).

Article  CAS  PubMed  Google Scholar 

Biancon, G. et al. Precision analysis of mutant U2AF1 activity reveals deployment of stress granules in myeloid malignancies. Mol. Cell 82, 1107–1122.e7 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Koschade, S. E. et al. Translatome proteomics identifies autophagy as a resistance mechanism to on-target FLT3 inhibitors in acute myeloid leukemia. Leukemia 36, 2396–2407 (2022).

Article  CAS  PubMed