PgenePapers _beta

This Shiny app is made by Achal Awasthi and Yan Zhang. Data tables are generated by Shenglong Tan and Acha Awasthi.
This app is under development and refinement. The visualization has been tested on R version 3.4.2 and Safari on Mac. Please drop an email at [email protected] to report an issue.

Reference: Awasthi A, Tan S, Travis JS, Mo X-M, Fan K, Zhang Y. PgenePapers: a novel database and search tools of reported regulatory pseudogenes. Submitted.

What is PgenePapers?

PgenePapers is a novel database and search tools of reported regulatory pseudogenes. We used all the currently available publications related to pseudogenes in PubMed, and mined the pseudogene-coding gene regulation pairs. We further assigned the pairs into different categories based on pseudogenes and their functional roles. We anticipate this study to set a foundation of systematically annotating regulatory pseudogenes, and facilitate future methodology development and experimental studies of pseudogene functions.

Database and Search Tools:

• Database Version - The publication titles and abstracts that we used were downloaded from PubMed on Oct. 27, 2017.

• Web Application Version - Beta version.

• Pseudogene-Gene-Role Table - Displays manually curated (based on computer generated results) pseudogene-coding gene regulation pairs, supports keyword search in the fly.

• All Papers - Displays manually curated (based on computer generated results) pseudogene-coding gene regulation pairs, provides abstract from publications as a reference, supports keyword search in the fly.

• NLP Network - The users can select one or all pseudogene(s) or genes (s) from the input lists, and generate an association network in the fly. Users can also download the filtered data corresponding to the graph.

• Gene-Pseudogene Correlation Table - Displays (spearman) correlation between genes and pseudogenes in all cancer types (mentioned in TCGA) based on manually curated pseudogene-coding gene regulation pairs. Also, gives the distribution of correlations and shows strongly correlated gene-pseudogene pairs for all cancer types. The TCGA gene and pseudogene expression data for all cancer types was downloaded from dreamBase database (Synapse ID: syn11461899).

• miRNA-Gene Correlation Table - Displays (spearman) correlation between genes and miRNA in all cancer types. Also, gives the distribution of correlations, miRNA-gene pairs based on predicted databases and shows strongly correlated miRNA-gene pairs for all cancer types. We downloaded the correlation among miRNAs and genes/pseudogenes from FireBrowse (http://firebrowse.org).

• Drug-Gene Table - Displays genes and the associated drugs with the coding gene for all cancer types mentioned in the TCGA. All the drugs mentioned in thge table are are FDA approved. We used the Drug Gene Interaction Database (DGIdb) version 3.0 (http://www.dgidb.org).

• Gene-pseudogene-miRNA-drug Network - The users can select one or all pseudogene(s) or genes (s) in addition to selecting miRNA(s) or drug (s) from the input lists, and generate an association network in the fly. Users can also download the filtered data corresponding to the graph.

• Latest Papers - Allows the users to stay up-to-date with the current psedogene research by displaying all the papers that were published after 2017.

• Readme - You are here.

• FAQ - This helps users asnwer questions about using the app.

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Developed and maintained by the Zhang Lab of Computational Genomics and Proteomics @ The Ohio State University. link