updated the paper

Author: ialbert

Makefile

@@ -41,9 +41,6 @@ tag: test
 exe: test
 	python src/genescape/exe.py --build
 
-shiny: test
-	pip install rsconnect
-	rsconnect deploy shiny src/genescape --name biostar --title GeneScape
 
 # Generate images for the documentation
 docimg:
@@ -63,8 +60,6 @@ fix:
 push:
 	git commit -am 'saving work' && git push
 
-
-
 build: clean
 	rm -rf build dist
 	hatch build 
@@ -106,6 +101,10 @@ clean:
 	rm -rf build dist ${IDX_FILE}
 
 env:
-	conda create -n genescape python=3.11 shiny rsconnect graphviz
+	micromamba create -n shiny python=3.11 rsconnect-python graphviz make -y
+
+shiny:
+	cp -f src/genescape/web.py src/app/app.py
+	rsconnect deploy shiny src/app --name biostar --title GeneScape
 
 .PHONY: test lint fix push clean build publish obo docimg web

README.md

@@ -8,6 +8,10 @@
 
 **GeneScape** is a Python-based [Shiny][pyshiny] application that be run both at the command line and also via a graphical user interface.
 
+There is a public version of the software at:
+
+* https://biostar.shinyapps.io/genescape/
+
 [pyshiny]: https://shiny.posit.co/py/
 
 ## Quickstart

docs/paper.bib

@@ -92,3 +92,13 @@ @ebi.ac.uk;
     eprint = {https://academic.oup.com/bioinformatics/article-pdf/25/22/3045/48997998/bioinformatics\_25\_22\_3045.pdf},
 }
 
+@InProceedings{networkx,
+  author =       {Aric A. Hagberg and Daniel A. Schult and Pieter J. Swart},
+  title =        {Exploring Network Structure, Dynamics, and Function using NetworkX},
+  booktitle =   {Proceedings of the 7th Python in Science Conference},
+  pages =     {11 - 15},
+  address = {Pasadena, CA USA},
+  year =      {2008},
+  editor =    {Ga\"el Varoquaux and Travis Vaught and Jarrod Millman},
+}
+

docs/paper.md

@@ -25,9 +25,9 @@ bibliography: paper.bib
 
 The Gene Ontology (GO)  [@Ashburner2000; @GO2023] is a structured vocabulary that describes gene products in the context of their associated functions. The ontology takes the form of a directed graph, where each node defines a term, and each edge represents a hierarchical relationship between the terms (the words of the vocabulary).
 
-For example, in the GO data, `GO:0090630` defines *activation of GTPase activity* and is a child of `GO:0043547`, which is a *positive regulation of GTPase activity* which in turn is a child of `GO:0051345` representing a *positive regulation of hydrolase activity*. 
+For example, in the GO data, `GO:0090630` defines *activation of GTPase activity* and is a child of `GO:0043547`, defined as *positive regulation of GTPase activity* which in turn is a child of `GO:0051345` representing *positive regulation of hydrolase activity*. 
 
-Gene association files (GAF) are text files used to annotate an organism's gene products with Gene Ontology terms, associating a function to a gene product. For example, a GAF file connects a gene product label, such as `ZC3H11B`, with multiple GO terms, such as `GO:0046872` or `GO:0016973`. The complete human genome GAF representation contains 288,575 associations of 19,606 gene symbols over 18,680 GO terms.
+Gene association files (GAF) are text files used to annotate an organism's gene products with Gene Ontology terms, associating a function to a gene product. For example, a GAF file connects a gene product label, such as `ZC3H11B`, with multiple GO terms, such as `GO:0046872` or `GO:0016973`. The complete human genome GAF representation contains 288,575 associations of 19,606 gene symbols with over 18,680 GO terms.
 
 The [Gene Ontology Consortium][GO] maintains GAF files for various organisms. Typical genomic analysis protocols generate gene lists that must be placed in a functional context. 
 
@@ -39,12 +39,14 @@ The most annotated gene in the human genome, `HTT1`, currently has 1098 annotati
 
 Web-based tools designed to visualize and filter gene ontology data include `AmiGO` [@AmiGO] and `QuickGO` [@QuickGO]. Command line tools like `goatools` [@goatools] support GO term lineage visualization. R packages like `topGO` [@topGO] implement GO structure visualizations of enriched GO terms. We are unaware of locally installable software that specifically allows for interactive filtering and visualization of gene ontology derived on gene lists.
 
-GeneScape is a Python package that allows users to visualize a list of gene products in terms of the functional context represented by the Gene Ontology. GeneScape is distributed both as a command-line tool and as GUI-enabled standalone software that does not require Python to be installed on the user's computer, thus making it accessible to a wide range of users.
+GeneScape is a Python package that allows users to visualize a list of gene products in terms of the functional context represented by the Gene Ontology. GeneScape is distributed both as a command-line tool and as GUI-enabled standalone software via the [Shiny platform][shiny], thus making it accessible to a wide range of users.
+
+[shiny]: https://shiny.posit.co/
 
 GeneScape is distributed with prebuilt databases for human and mouse genomes. For other organisms, users need to download the GAF files from the Gene Ontology website and run the command:
 
 ```
-genescape build --gaf mydata.gaf --index mydata.index.gz 
+genescape build --gaf mydata.gaf.gz --index mydata.index.gz 
 ```
 
 The `build` command will create a database that can then be used for all subsequent analyses with the software. Users should consult the [GeneScape documentation][docs] for up-to-date details. 
@@ -64,17 +66,18 @@ GRTP1
 GeneScape first transforms the above gene input list into a GO term list, where additional information is added to each term:
 
 ```
-gid,root,count,function,source,size,label
-GO:0090630,BP,1,activation of GTPase activity,GRTP1,4,(1/4)
-GO:0046982,MF,1,protein heterodimerization activity,ABTB3,4,(1/4)
-GO:0031083,CC,1,BLOC-1 complex,BCAS4,4,(1/4)
-GO:0016020,CC,1,membrane,ABTB3,4,(1/4)
-GO:0005737,CC,1,cytoplasm,BCAS4,4,(1/4)
-GO:0005615,CC,1,extracellular space,C3P1,4,(1/4)
-...
+count,function,root,goid,source,size,label
+1,activation of GTPase activity,BP,GO:0090630,GRTP1,4,(1/4)
+1,protein heterodimerization activity,MF,GO:0046982,ABTB3,4,(1/4)
+1,BLOC-1 complex,CC,GO:0031083,BCAS4,4,(1/4)
+1,membrane,CC,GO:0016020,ABTB3,4,(1/4)
+1,cytoplasm,CC,GO:0005737,BCAS4,4,(1/4)
+1,extracellular space,CC,GO:0005615,C3P1,4,(1/4)
+1,GTPase activator activity,MF,GO:0005096,GRTP1,4,(1/4)
+1,endopeptidase inhibitor activity,MF,GO:0004866,C3P1,4,(1/4)
 ```
 
-In the next step, GeneScape visualizes the GO terms as the graph structure that represents the functional context of the genes relative to the larger Gene Ontology.
+In the next step, GeneScape draws the GO terms as the graph structure using the Networkx package [@networkx] helping users visualize the functional context of the genes relative to the larger Gene Ontology.
 
 ![Ontology subgraph for a gene list \label{fig:interface}](images/genescape-output1.png){height="216pt"}
 
@@ -83,9 +86,9 @@ Various colors are used to provide additional context to the nodes in the graph;
 Since the resulting graphs may also be large, with thousands of nodes, the main interface provides input widgets that allow users to interactively 
 reduce the subgraph to nodes for which:
 
-1. The function definitions match certain patterns
-2. A minimum number of genes share a function, 
-3. Nodes belong to a specific GO subtree: Biological Process (BP), Molecular Function (MF), Cellular Component (CC)
+1. The function definitions match certain patterns.
+2. A minimum number of genes share a function. 
+3. Nodes belong to a specific GO subtree: Biological Process (BP), Molecular Function (MF), Cellular Component (CC).
 
 As an example, take the input genelist of just four genes:
 

src/app/requirements.txt

@@ -0,0 +1 @@
+genescape