An expression atlas of human primary cells: inference of gene function from coexpression networks

By Bmc Genomics, N. Mabbott, Kenneth Baillie, H. Brown, Tom C. Freeman, D. A. Hume. BMC Genomics, 2013

421 citations recorded by the source corpus.

The specialisation of mammalian cells in time and space requires genes associated with specific pathways and functions to be co-ordinately expressed. Here we have combined a large number of publically available microarray datasets derived from human primary cells and analysed large correlation graphs of these data. Using the network analysis tool BioLayout Express3D we identify robust co-associations of genes expressed in a wide variety of cell lineages. We discuss the biological significance of a number of these associations, in particular the coexpression of key transcription factors with the genes that they are likely to control. We consider the regulation of genes in human primary cells and specifically in the human mononuclear phagocyte system. Of particular note is the fact that these data do not support the identity of putative markers of antigen-presenting dendritic cells, nor classification of M1 and M2 activation states, a current subject of debate within immunological field. We have provided this data resource on the BioGPS web site (http://biogps.org/dataset/2429/primary-cell-atlas/) and on macrophages.com (http://www.macrophages.com/hu-cell-atlas).

Subfields: Immunology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/11fccf22fbe98afa768a87cb47e36ae85e6639a9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Immunology

1. Atul J. Butte
2. Zicheng Hu
3. D. Aran

In Molecular Biology

1. Hui Shen
2. Atul J. Butte
3. Jun S. Liu
4. X. S. Liu
5. Chunlei Wu
6. Zicheng Hu
7. D. Aran
8. Michael B. Yaffe

Citations in the corpus

• BioGPS: building your own mash-up of gene annotations and expression profiles (2015, background): “Additional sub-portals have been created focusing on circadian rhythm studies (7) and primary cells gene expression (8).”
• xCell: digitally portraying the tissue cellular heterogeneity landscape (2017, methodology): “Raw Affymetrix microarray CEL files were downloaded from the Gene Expression Omnibus (GEO), accessions: GSE22886 (IRIS), GSE24759 (Novershtern) and GSE49910 (HPCA), and analyzed using the Robust Multi-array Average (RMA) procedure on probe-level data using Matlab functions.”
• Comprehensive analyses of tumor immunity: implications for cancer immunotherapy (2016, methodology): “(XLSX 43 kb) Abbreviations ACC, adenocortical carcinoma; BLCA, bladder carcinoma; BRCA, breast carcinoma; CESC, cervical squamous carcinoma; COAD, colon adenocarcinoma; CT, cancer/testis; CTL, cytotoxic T cell; CYT, cytolytic activity; DLBC, diffusive large B-cell lymphoma; GBM, glioblastoma multifo”