Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Gene Expression Commons: an open platform for absolute gene expression profiling

ABSTRACT: Gene expression profiling using microarray has been limited to profiling of differentially expressed genes at comparison setting since probesets for different genes have different sensitivities. We overcome this limitation by using a very large number of varied microarray datasets as a common reference, so that statistical attributes of each probeset, such as dynamic range or a threshold between low and high expression can be reliably discovered through meta-analysis. This strategy is implemented in web-based platform named “Gene Expression Commons” (http://gexc.stanford.edu/ ) with datasets of 39 distinct highly purified mouse hematopoietic stem/progenitor/functional cell populations covering almost the entire hematopoietic system. Since the Gene Expression Commons is designed as an open platform, any scientist can explore gene expression of any gene, search by expression pattern of interest, submit their own microarray datasets, and design their own working models.

ORGANISM(S): Mus musculus

PROVIDER: GSE34723 | GEO | 2012/07/18

SECONDARY ACCESSION(S): PRJNA150429

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Gene Expression Commons: an open platform for absolute gene expression profiling

Project description:Gene expression profiling using microarray has been limited to profiling of differentially expressed genes at comparison setting since probesets for different genes have different sensitivities. We overcome this limitation by using a very large number of varied microarray datasets as a common reference, so that statistical attributes of each probeset, such as dynamic range or a threshold between low and high expression can be reliably discovered through meta-analysis. This strategy is implemented in web-based platform named “Gene Expression Commons” (http://gexc.stanford.edu/ ) with datasets of 39 distinct highly purified mouse hematopoietic stem/progenitor/functional cell populations covering almost the entire hematopoietic system. Since the Gene Expression Commons is designed as an open platform, any scientist can explore gene expression of any gene, search by expression pattern of interest, submit their own microarray datasets, and design their own working models. Gene expression profiling of entire mouse hematopoiesis system (39 populations) by Gene Expression Commons system. The Samples (101) below comprise new and re-processed data and represent 37 populations. The complete dataset comprising new, re-processed, and third-party reanalyzed data (107 samples), and representing all 39 populations, is linked below as a supplementary file.

2012-07-17 | E-GEOD-34723 | biostudies-arrayexpress

Mus musculus

Project description:Gene Expression Commons: an open platform for absolute gene expression profiling

| PRJNA150429 | ENA

Hematopoietic stem cell quiescence attenuates DNA damage repair and response contributing to age-dependent DNA damage accumulation

Project description:Comprehensive analysis of gene expression in hematopoietic stem and progenitor cells from young and old mice. Gene expression profiling of young and old mouse hematopoietic stem and progenitor cells by Gene Expression Commons system.

2014-05-08 | E-GEOD-55525 | biostudies-arrayexpress

Global transcriptional profiling reveals distinct functions of thymic stromal subsets and age-related changes during thymic involution

Project description:The thymic microenvironment is essential for proper differentiation and selection of thymocytes.Thymic involution in aged mice results in decreased T cell output and immune function. Here we use gene expression profiling of FACS sorted thymic stromal subsets to identify molecular mediators of thymocyte: stromal cell interactions, as well as gene expression changes thymic stromal subsets during early stages of thymic involution . We used microarrays to analyze gene expression differences between thymic stromal subsets from male C57BL/6J mice 1, 3, and 6 months of age. Thymic stromal subsets (cTEC, mTEClo, mTEChi, Sirpa-DC, Sirpa+DC, and fibroblasts) were isolated from two 1-, 3-, and 6- month old male C57BL/6J mice. After enzymatic digestion of the thymi, the stromal cells were FACS purified, and RNA was extracted, amplified, labeled and hybridized to Affymetrix mouse 430 2.0 arraysarrays. Raw data were uploaded to Gene Expression Commons for normalization. Both raw CEL and normalized datasets from the 36 samples are included. A model within Gene Expression Commons has been created for analyses/comparisons of these datasets, along with previously reported thymocyte subset datasets. The model within Gene Expression Commons thus contains 6 thymic stromal populations, each from mice 1, 3, and 6 months of age, with duplicates for each datset.

2014-09-12 | E-GEOD-56928 | biostudies-arrayexpress

Expression Profiling of Primary Human Proerythroblasts (ProEs) After IRF2, IRF6, and MYB shRNA Knockdown

Project description:IRF2, IRF6, and MYB are candidate regulators of human erythropoiesis. We here examine primary CD34+ hematopoietic stem/progenitor cells (HSPCs)-derived erythroid progenitors with control, IRF2, IRF6, or MYB shRNA lentiviral transduction prior to differentiation. Gene expression microarray profiling datasets for MYB shRNA and control shRNA were obtained from Gene Expression Omnibus (GEO) under accession number GSE25678. The data were analyzed together with the datasets obtained in this study. Primary maturing adult erythroblasts were generated ex vivo from CD34+ hematopoietic stem/progenitor cells (HSPCs) using a serum-free two-phase liquid culture system. CD34+ HSPCs were transduced with lentiviruses containing shRNAs against IRF2 or IRF6 gene, selected and differentiated to proerythroblasts (ProEs). Cells were harvested at day 5 of differentiated and total RNA were extracted. This was used to hybridize to Affymetrix expression arrays using the HG-U133 Plus 2.0 platform.

2012-10-05 | E-GEOD-36988 | biostudies-arrayexpress

Diagnosis and early detection of CNS-SLE in MRL/lpr mice using peptide microarrays (GPL17600)

Project description:In addition to determining possible diagnostic and predictive peptides of lupus and CNS-lupus, we also used our microarray technology along with the Guitope computer program to determine possible natural protein match to five monoclonal autoantibodies that were created using one of the autoimmune MRL/lpr mouse. Submitter states "We have no processed data to submit. We have no gpr files to submit." Microarray analysis was performed on five monoclonal brain-reactive autoantibodies (F9, G10, G4, D1 and D9) that were created from one autoimmune mouse with altered behavior. These samples were tested in duplicated along with a control sample on the GPL17600 platform.

2014-05-08 | E-GEOD-57389 | biostudies-arrayexpress

Construction of brest cancer cell line BT20-specific interactome

Project description:Experiment type: Expression profiling by microarray and RNA-seq data, Third-party re-analysis The purpose of our study is to construct breast cancer cell line BT20-specific interactome by aggregating publically available microarray or RNA-seq samples, and identify novel transcriptional regulators that control breast cancer progression. We collected 101 samples of BT20 cell line microarray or RNA-seq from 12 prior studies and our own study data, GSE120919. We performed normalization for Affymetrix microarray platform and Illumina HiSeq and NovaSeq platform datasets. For the normalization, we used SCAN.UPC R package (ver.2.24.0, PMID: 22959562, https://www.bioconductor.org/packages/release/bioc/html/SCAN.UPC.html) on Affymetrix microarray platform datasets. We use Rsubread R package (ver.1.30.5, PMID: 23558742, http://bioconductor.org/packages/Rsubread/), TPM log2 values on Illumina HiSeq and NovaSeq platform datasets. And then, we performed batch effect adjusting to combine the datasets which came from different laboratories. The matrix data we deposited in GEO has normalized log2 signal intensity for 12,360 genes, and the genes were mapped to human Entrez Gene IDs that overlapped across 13 datasets (a total number of 101 samples). BT20-specific interactome was assembled by Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe, PMID: 16723010). Then, we used Master Regulator Analysis-Fisher?s Extact Test (MRA-FET, PMID: 20531406) to infer transcription factors which control a gene signature dysregulated by a fusion gene in BT20 cell line (please refer to GSE120919). We discovered SNAI2 as a master regulator candidate to modulate the gene signature in the fusion gene expressing BT20. Our findings will provide biological insights into the role of the fusion gene in breast cancer.

2020-03-28 | GSE123917 | GEO

Expression Profiling of Primary Human Proerythroblasts (ProEs) After IRF2, IRF6, and MYB shRNA Knockdown

2012-10-05 | GSE36988 | GEO

Diagnosis and early detection of CNS-SLE in MRL/lpr mice using peptide microarrays (GPL17600)

2014-05-08 | GSE57389 | GEO

Gene expression datasets

Project description:Gene expression datasets

| PRJNA785808 | ENA