GEO 数据库
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Does GEO store raw data?
Yes. GEO requires raw data, processed data and metadata. Raw data facilitates the unambiguous interpretation of the data and potential verification of conclusions. For microarray data, raw data may be supplied either within the Sample record data tables or as external supplementary data files, e.g., Affymetrix CEL. For high-throughput sequencing, GEO brokers the complete set of raw data files, e.g., FASTQ, to the SRA database on your behalf.GEO如果存的是NGS数据 那么原始数据在SRA上
如何关联GEO和SRA?
https://www.researchgate.net/figure/The-GEO-and-SRA-simple-search-interface-and-search-results-A-The-Simple-Search_fig1_337316408http://homer.ucsd.edu/homer/basicTutorial/retrieveFiles.html
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https://github.com/s-andrews/sradownloader
A script to make downloading of SRA/GEO data easier -
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https://www.qlucore.com/import-and-analyze-public-data-from-sra-geo-and-tcga
Import and analyze public data from SRA, GEO and TCGA -
https://www.nature.com/articles/s41598-019-43935-8
GREIN: An Interactive Web Platform for Re-analyzing GEO RNA-seq Datahttps://github.com/uc-bd2k/GREP2
GEO RNA-seq Experiments Processing Pipeline 一个R实现的pipeline 处理了geo的数据

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https://ncbiinsights.ncbi.nlm.nih.gov/2021/10/21/geo-sra-dbgap-tracks-genome-data-viewer/
View GEO, SRA, or dbGaP data tracks in NCBI’s Genome Data Viewer -
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https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-018-2308-x
BART: bioinformatics array research tool -
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GEORAC: an RNA-seq Atlas Constructor for the
Gene Expression Omnibus
https://dc.uwm.edu/cgi/viewcontent.cgi?article=2880&context=etd -
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https://www.nature.com/articles/sdata2017125
Precision annotation of digital samples in NCBI’s gene expression omnibus
http://stargeo.org/ 对GEO的所有样本做了标签化注释 -
https://academic.oup.com/bioinformatics/article/28/8/1184/194911
RNA-Seq Atlas—a reference database for gene expression profiling in normal tissue by next-generation sequencing -
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https://www.ncbi.nlm.nih.gov/labs/pmc/articles/PMC6333964/
Restructured GEO: restructuring Gene Expression Omnibus metadata for genome dynamics analysis
http://www.regeo.org
对GEO做了文本挖掘增加了时间线和疾病功能


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https://link.springer.com/article/10.1007/s12551-018-0490-8
Mining data and metadata from the gene expression omnibus
对GEO数据的挖掘做了详细分析
里面提到了一些二次挖掘的工具列表
https://link.springer.com/article/10.1007/s12551-018-0490-8/tables/1

metadata的三种提炼思路:

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一些可以用的git库
https://github.com/guma44/GEOparse
python实现 对标geoquery -

