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gene_networks_inference [2019/03/07 02:07] – [Data] admingene_networks_inference [2019/06/03 16:16] – [Software] admin
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 **Pigengene:** This R package provides an efficient way to perform network analysis and to infer biological signatures from gene expression profiles. The signatures are independent from the underlying platform, e.g., it can infer the signatures using data from microarray and evaluate them in an independent RNA Seq dataset. It is approved by, and publicly available from, [[https://bioconductor.org/packages/Pigengene|Bioconductor]]. **Pigengene:** This R package provides an efficient way to perform network analysis and to infer biological signatures from gene expression profiles. The signatures are independent from the underlying platform, e.g., it can infer the signatures using data from microarray and evaluate them in an independent RNA Seq dataset. It is approved by, and publicly available from, [[https://bioconductor.org/packages/Pigengene|Bioconductor]].
  
-**iNETgrate:** [[https://bitbucket.org/habilzare/genetwork/src/master/code/iNETgrate/|This]] R package is useful to integrate DNA methylation and gene expression data into //a single //network. This approach leads to identification of more robust gene modules compared to conventional coexpression networks. The package will be publicly available after review and approval by Bioconductor.+**iNETgrate:** This R package is useful to integrate DNA methylation and gene expression data into //a single //network [[[https://bitbucket.org/habilzare/genetwork/src/master/|code]]]. This approach leads to identification of more robust gene modules compared to conventional coexpression networks. The package will be publicly available after review and approval by Bioconductor.
  
  
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   - [[https://amp.pharm.mssm.edu/archs4/|ARCHS4]], which was developed at the Icahn School of Medicine at Mount Sinai, and provides tools to download and analyze RNA-Seq data including single-cell gene expression.   - [[https://amp.pharm.mssm.edu/archs4/|ARCHS4]], which was developed at the Icahn School of Medicine at Mount Sinai, and provides tools to download and analyze RNA-Seq data including single-cell gene expression.
   - The [[https://www.nature.com/articles/s41586-018-0623-z#Sec38|BEAT]] ALM dataset of ~300 cases including gene expression, survival, ELN17, etc.   - The [[https://www.nature.com/articles/s41586-018-0623-z#Sec38|BEAT]] ALM dataset of ~300 cases including gene expression, survival, ELN17, etc.
- +  - [[https://www.leukemiaatlas.org/adultaml|Leukemia Protein Atlas]]: Expression of hundreds of proteins were measured in bone marrow and PB samples of ~200 AML cases. A good publicly available resource to validate findings based on gene expression assays.
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