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Archive notice

This GitHub repository is archived. Development of the artifacts will continue in the following projects:

fasta-playground

fasta-playground demonstrates sequence library searching via the FASTA package, result processing and visualization using Java Server Faces (JSF). This is a spin-off project of the CRIMSy (Cloud Resource & Information Management System).

UI design was inspired by SequenceServer and EBI's Sequence Similarity Searching Tools.

Docker setup

Note: This is a multi-stage build and requires Docker version ≥ 17.05.

Build the image: docker build -t fasta-playground -f docker/Dockerfile .

Remove intermediate images from the build: docker image prune --filter label=stage=fasta-playground-builder

Start a container: docker run -itp 8080:8080 --rm --name fasta-playground fasta-playground (add -d for detached mode) and browse to http://localhost:8080/Fasta-Playground/LibrarySearch.xhtml.

Non-Docker setup

Requires a JDK Version ≥ 8, Apache Maven, gcc, glibc and make.

Download and compile the fasta36 package and alter the path to fasta36's bin directory in SearchFactory.java (field FASTA_BIN_DIRECTORY) accordingly.

Deployment via embedded Java EE application server

cd ui, run either mvn clean package tomee-embedded:run (embedded TomEE with MyFaces as JSF implementation) or mvn clean package embedded-glassfish:run (embedded GlassFish with Mojarra as JSF implementation) and browse to http://localhost:8080/Fasta-Playground/LibrarySearch.xhtml.

Deployment on a Java EE application server

cd ui, run mvn clean package and deploy target/Fasta-Playground.war on a Java EE application server (requires at least Java EE 7 Web Profile with JSF 2.2).