GEO studies.zip
收藏DataCite Commons2021-10-05 更新2024-07-28 收录
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https://figshare.com/articles/dataset/GEO_studies_zip/16736725
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资源简介:
Here, we reanalysed a total of 27 GEO studies to identify and annotate lung cancer versus normal signatures, as well as single-gene perturbation, and single-drug perturbation signatures. Differential expression within each category was computed using GEO2Enrichr and the Characteristic Direction method. We identified the co-DEGs across different studies within each category, and their upstream regulating kinases and TFs using Expression2Kinases.
本研究共重新分析了27项基因表达综合数据库(Gene Expression Omnibus,GEO)的研究,旨在鉴定并注释肺癌与正常组织的特征基因集、单基因扰动特征集以及单药物扰动特征集。我们采用GEO2Enrichr与特征方向法(Characteristic Direction Method)计算了各分类下的差异表达情况。随后借助Expression2Kinases工具,我们鉴定出了各分类下不同研究间的共差异表达基因(co-differentially expressed genes,co-DEGs),以及这些基因的上游调控激酶与转录因子(Transcription Factors,TFs)。
提供机构:
figshare
创建时间:
2021-10-05



