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Prediction of Experimental Metadata from Gene Expression

Pipeline

  • Data collection from [GEO] library
  • Annotations of Platforms

GEOparse

Installation:

pip install GEOparse

[Usage:]

gse = GEOparse.get_GEO(geo="GSE1563", destdir="./")

gse.gsms.items()  # pairs of `gsm_name` and `gsm`
gse.gpls.items()  # pairs of `gpl_name` and `gpl`
GEO Terms
  • GSE (Series) is a record that summarizes whole study including samples and platforms
    • GPL (Platform) contains mappings from probe IDs to RefSeq IDs
    • GSM (Sample) contains information about the conditions and preparation of a Sample
[source of image: http://slideplayer.com/slide/4814436/]

Methods

References

  • Improving the value of public RNA-seq expression data by phenotype prediction [bioRxiv]
  • MAnorm: a robust model for quantitative comparison of ChIP-Seq data sets [BioMed Central]
  • A Python module to normalize microarray data by the quantile adjustment method [PubMed Central]

License

Copyright © 2017, BioinfoGroup. Released under the GNU AGPLv3.