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Concept Whitepaper
SchSascha edited this page May 15, 2018
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This document contains the conceptual background and realization plans for the GePi publication.
- Use ElasticSearch index with new mapping structure
- Incorporate daily updates
- Build GePi Pipeline
- Let run daily
- A Search
- A-B-Search
- Gene IDs
- UniProt IDs?
- Gene Names?
- Mapping to top homology
- Rather do mapping by gene name?
- Make sure the algorithms do what they are supposed to! Write tests!
- How to deal with enlargening the widget? When the widget is larger, more edges could be shown. But: How many? Depends on number of nodes and the size of the nodes, i.e. the abundances
- Same as with simple sankey chart
- How to rank common partner pairs, i.e. which pairs to show?
- Currently: a and b have common partner c ->
score(a,b,c) = #(a,c) + #(b,c)
- downside is that unbalanced hits are not ranked: weighting the score with
max(#(a,c) / #(b,c), #(b,c) / #(a,c)) * 2
could be an option (should be in (0,1] )
- downside is that unbalanced hits are not ranked: weighting the score with
- Allow sentence filtering by key words
- Provide abundance tables
- A-Search: provide abundance of all interaction partners
- A-B-Search:
- show abundance of A and B members, possibly in separate columns
- show number of different interaction partners for A and B members (potentially including median and/or mean+std)
Usage and Advantage of GePi Capabilities
Use Cases
- Proteomics
- Transcriptomics?
- Pathways - potential interaction partner?
Evaluation
- NatComm scenario against EvexDB
- Evaluate with event-corpora