Gene Expression Commons: an open platform for absolute gene expression profiling.
Gene expression profiling using microarrays has been limited to comparisons of gene expression between small numbers of samples within individual experiments. However, the unknown and variable sensitivities of each probeset have rendered the absolute expression of any given gene nearly impossible to...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2012-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC3399844?pdf=render |
| _version_ | 1831760791924113408 |
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| author | Jun Seita Debashis Sahoo Derrick J Rossi Deepta Bhattacharya Thomas Serwold Matthew A Inlay Lauren I R Ehrlich John W Fathman David L Dill Irving L Weissman |
| author_facet | Jun Seita Debashis Sahoo Derrick J Rossi Deepta Bhattacharya Thomas Serwold Matthew A Inlay Lauren I R Ehrlich John W Fathman David L Dill Irving L Weissman |
| author_sort | Jun Seita |
| collection | DOAJ |
| description | Gene expression profiling using microarrays has been limited to comparisons of gene expression between small numbers of samples within individual experiments. However, the unknown and variable sensitivities of each probeset have rendered the absolute expression of any given gene nearly impossible to estimate. We have overcome this limitation by using a very large number (>10,000) of varied microarray data as a common reference, so that statistical attributes of each probeset, such as the dynamic range and threshold between low and high expression, can be reliably discovered through meta-analysis. This strategy is implemented in a web-based platform named "Gene Expression Commons" (https://gexc.stanford.edu/) which contains data of 39 distinct highly purified mouse hematopoietic stem/progenitor/differentiated cell populations covering almost the entire hematopoietic system. Since the Gene Expression Commons is designed as an open platform, investigators can explore the expression level of any gene, search by expression patterns of interest, submit their own microarray data, and design their own working models representing biological relationship among samples. |
| first_indexed | 2024-12-22T04:37:49Z |
| format | Article |
| id | doaj.art-1d3c27656acd427fb3d9f13a4c82650d |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-22T04:37:49Z |
| publishDate | 2012-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-1d3c27656acd427fb3d9f13a4c82650d2022-12-21T18:38:51ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-0177e4032110.1371/journal.pone.0040321Gene Expression Commons: an open platform for absolute gene expression profiling.Jun SeitaDebashis SahooDerrick J RossiDeepta BhattacharyaThomas SerwoldMatthew A InlayLauren I R EhrlichJohn W FathmanDavid L DillIrving L WeissmanGene expression profiling using microarrays has been limited to comparisons of gene expression between small numbers of samples within individual experiments. However, the unknown and variable sensitivities of each probeset have rendered the absolute expression of any given gene nearly impossible to estimate. We have overcome this limitation by using a very large number (>10,000) of varied microarray data as a common reference, so that statistical attributes of each probeset, such as the dynamic range and threshold between low and high expression, can be reliably discovered through meta-analysis. This strategy is implemented in a web-based platform named "Gene Expression Commons" (https://gexc.stanford.edu/) which contains data of 39 distinct highly purified mouse hematopoietic stem/progenitor/differentiated cell populations covering almost the entire hematopoietic system. Since the Gene Expression Commons is designed as an open platform, investigators can explore the expression level of any gene, search by expression patterns of interest, submit their own microarray data, and design their own working models representing biological relationship among samples.http://europepmc.org/articles/PMC3399844?pdf=render |
| spellingShingle | Jun Seita Debashis Sahoo Derrick J Rossi Deepta Bhattacharya Thomas Serwold Matthew A Inlay Lauren I R Ehrlich John W Fathman David L Dill Irving L Weissman Gene Expression Commons: an open platform for absolute gene expression profiling. PLoS ONE |
| title | Gene Expression Commons: an open platform for absolute gene expression profiling. |
| title_full | Gene Expression Commons: an open platform for absolute gene expression profiling. |
| title_fullStr | Gene Expression Commons: an open platform for absolute gene expression profiling. |
| title_full_unstemmed | Gene Expression Commons: an open platform for absolute gene expression profiling. |
| title_short | Gene Expression Commons: an open platform for absolute gene expression profiling. |
| title_sort | gene expression commons an open platform for absolute gene expression profiling |
| url | http://europepmc.org/articles/PMC3399844?pdf=render |
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