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Comprehensive comparison of large-scale tissue expression datasets
Open accessPreprint — published as 10.7717/peerj.1054 · Paper page
Abstract
For tissues to carry out their functions, they rely on the right proteins to be present. Several high-throughput technologies have been used to map out which proteins are expressed in which tissues; however, the data have not previously been systematically compared and integrated. We present a comprehensive evaluation of tissue expression data from a variety of experimental techniques and show that these agree surprisingly well with each other and with results from literature curation and text mining. We further found that most datasets support the assumed but not demonstrated distinction between tissue-specific and ubiquitous expression. By developing comparable confidence scores for all types of evidence, we show that it is possible to improve both quality and coverage by combining the datasets. To facilitate use and visualization of our work, we have developed the TISSUES resource ( http://tissues.jensenlab.org ), which makes all the scored and integrated data available through a single user-friendly web interface.
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Li, J. J., Bickel, P. J., & Biggin, M. D. (2014) · PeerJ · doi:10.7717/peerj.270 · Cited by 279
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- 1991, Complementary DNA sequencing: expressed sequence tags and human genome project, Science (New York, N.Y.), 252, 1651, 10.1126/science.2047873 · DOI
- 2002, Toward a Human Blood Serum Proteome: Analysis By Multidimensional Separation Coupled With Mass Spectrometry, Molecular & Cellular Proteomics, 1, 947, 10.1074/mcp.M200066-MCP200 · DOI
- 10.1186/gb-2008-9-2-r31 · DOI
- 2013, In-depth mass spectrometric mapping of the human vitreous proteome, Proteome science, 11, 22, 10.1186/1477-5956-11-22 · DOI
- 2012, Text mining in the biocuration workflow: applications for literature curation at WormBase, dictyBase and TAIR, DatabaseLJ: the journal of biological databases and curation, 2012, bas040
- 1998, Analysis of EST-driven gene annotation in human genomic sequence, Genome research, 8, 362, 10.1101/gr.8.4.362 · DOI
- 10.1093/nar/gkq1184 · DOI
- 10.1093/database/bau012 · DOI
- 10.1186/1471-2105-9-118 · DOI
- 10.1093/nar/gkt661 · DOI
- 10.1038/msb.2009.17 · DOI
- 2011, Non-specific binding of antibodies in immunohistochemistry: fallacies and facts, Scientific reports, 1, 28, 10.1038/srep00028 · DOI
- 10.1371/journal.pone.0022859 · DOI
- Churchill GA. 2002. Fundamentals of experimental design for cDNA microarrays. Nature genetics. · DOI
- 10.1186/gb-2007-8-4-r64 · DOI
- 2008, A comprehensive functional analysis of tissue specificity of human gene expression, BMC biology, 6, 49, 10.1186/1741-7007-6-49 · DOI
- 2013, Human housekeeping genes, revisited, Trends in geneticsLJ: TIG, 29, 569, 10.1016/j.tig.2013.05.010 · DOI
- 10.1021/pr101132h · DOI
- Ezkurdia I , Vázquez J. 2014. Analyzing the First Drafts of the Human Proteome. Journal of proteome …. · DOI
- 2014, Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics, Molecular & cellular proteomicsLJ: MCP, 13, 397, 10.1074/mcp.M113.035600 · DOI · Paper page
- 10.1093/nar/gks1094 · DOI · Paper page
- 10.1016/S1369-5274(00)00091-6 · DOI
- 10.1152/physiolgenomics.00040.2001 · DOI
- Kampf C , Olsson I , Ryberg U , Sjöstedt E , Pontén F. 2012. Production of tissue microarrays, immunohistochemistry staining and digitalization within the human protein atlas. Journal of visualized experimentsLJ: JoVE. · DOI
- 10.1093/nar/gkp936 · DOI
- 10.1038/nature13302 · DOI · Paper page
- 2009, TissueDistributionDBs: a repository of organism-specific tissue-distribution profiles, Theoretical Chemistry Accounts, 125, 651
- 10.1093/bioinformatics/bts084 · DOI
- 10.1073/pnas.0810772105 · DOI · Paper page
- 10.1038/ng887 · DOI
- 10.1152/physiolgenomics.00313.2005 · DOI
- Lipshutz RJ , Fodor SPA , Gingeras TR , Lockhart DJ. 1999. High density synthetic oligonucleotide arrays. Nature genetics. · DOI
- 10.1186/1471-2105-9-271 · DOI
- 10.1038/ng.2653 · DOI · Paper page
- 2012, Quantitative maps of protein phosphorylation sites across 14 different rat organs and tissues, Nature communications, 3, 876, 10.1038/ncomms1871 · DOI · Paper page
- 2012, Enhancing the prioritization of disease-causing genes through tissue specific protein interaction networks, PLoS computational biology, 8, e1002690, 10.1371/journal.pcbi.1002690 · DOI
- Nagalakshmi U , Waern K , Snyder M. 2010. RNA-Seq: a method for comprehensive transcriptome analysis. Current protocols in molecular biology / edited by Frederick M. Ausubel … [et al.] Chapter 4:Unit 4.11.1-13. · DOI
- 10.1093/bib/bbl015 · DOI
- 10.1371/journal.pone.0065390 · DOI · Paper page
- 2013, Mass spectrometry-based proteomics in molecular diagnostics: discovery of cancer biomarkers using tissue culture, BioMed research international, 2013, 783131
- 10.1038/msb.2009.93 · DOI · Paper page
- 2013, Adding protein context to the human protein-protein interaction network to reveal meaningful interactions, PLoS computational biology, 9, e1002860, 10.1371/journal.pcbi.1002860 · DOI
- 10.1186/gb-2006-7-11-242 · DOI
- 10.1093/nar/gks1049 · DOI
- 10.1158/1078-0432.CCR-0927-3 · DOI
- 10.1073/pnas.0801374105 · DOI
- 10.1186/gb-2005-6-3-r22 · DOI
- 10.1073/pnas.0400782101 · DOI · Paper page
- 10.1093/nar/gkt1140 · DOI
- 10.1126/science.1260419 · DOI · Paper page
- 10.1093/bioinformatics/btm102 · DOI
- 10.1038/nrg2484 · DOI · Paper page
- 2006, Data merging for integrated microarray and proteomic analysis, Briefings in functional genomics & proteomics, 5, 261, 10.1093/bfgp/ell019 · DOI
- 10.1093/nar/gkg033 · DOI
- 10.1038/nature13319 · DOI · Paper page
- 10.1186/gb-2009-10-11-r130 · DOI
- 10.1152/physiolgenomics.00178.2010 · DOI
- 10.1186/1471-2164-9-172 · DOI
- 2008, On the nature of human housekeeping genes, Trends in geneticsLJ: TIG, 24, 481, 10.1016/j.tig.2008.08.004 · DOI
Metadata
- Authors
- Santos, A., Tsafou, K., Stolte, C., Pletscher-Frankild, S., O’Donoghue, S. I., & Jensen, L. J.
- Affiliations
- University of Copenhagen (DK)
- Commonwealth Scientific and Industrial Research Organisation (AU)
- Venue
- PeerJ
- Publisher
- openRxiv
- Published
- 2014-11-10
- Volume
- 3
- Pages
- e1054-e1054
- ISSN
- 2167-8359 (ISSN-L)
- PMC
- PMC4493645
- OpenAlex
- W1700570096
- Cited by
- 92
- References
- 1
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 6 · 2023: 1 · 2022: 8 · 2021: 7 · 2020: 11 · 2019: 13 · 2018: 9 · 2017: 11 · 2016: 13 · 2015: 4
- FWCI
- 5.50
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PeerJ (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, other-oa)
- UNSWorks (UNSW Sydney) (submittedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Commonwealth Scientific and Industrial Research Organisation
- Novo Nordisk (NNF14CC0001)
- National Institutes of Health
- National Cancer Institute (U54CA189205)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Health Sciences › Medicine › Health Informatics › Biomedical Text Mining and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Keywords
- tissue-specific protein expression, data integration, confidence scores, literature curation, text mining, high-throughput proteomics, data quality assessment
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