This repository contains docker file to run FimTyper with linux docker image.
- move to FimTyper root directory(Dockerfile)
- docker build -t genomixcloud/fimtyper .
docker run --name fimtyper --rm -ti genomixcloud/fimtyper \
perl /usr/local/fimtyper/fimtyper.pl
ref: https://bitbucket.org/genomicepidemiology/fimtyper/src/master/README.md#usage
docker run --name fimtyper --rm -ti genomixcloud/fimtyper \
perl /usr/local/fimtyper/fimtyper.pl \
-d /usr/local/fimtyper/fimtyper_db -i \
/usr/local/fimtyper/test.fsa -k 95.00 -l 0.60
AWS S3
Mandatory
In Dockerfile file:
Under comment # install awscli add the following code:
RUN wget -P /usr/src/ https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip && \
unzip -d /usr/src/ /usr/src/awscli-exe-linux-x86_64.zip && \
rm /usr/src/awscli-exe-linux-x86_64.zip && \
/usr/src/aws/install && \
mkdir /src && mkdir /conf
Other considerations:
- The image contains 2 directories (/src, /conf).
- The /src/fimtyper.sh can include a call to FimTyper tool and in and out directories linked with AWS S3. The previous link can be configured in /conf folder
- With the previous configuration you can try run the commands below.
docker build -t ${your_own_workspace}/fimtyper .
docker run --name fimtyper --rm -ti \
-e AWS_ACCESS_KEY_ID="${AWS_ACCESS_KEY_ID}" \
-e AWS_SECRET_ACCESS_KEY="${AWS_SECRET_ACCESS_KEY}" \
--mount src="$(pwd)",target=/data,type=bind \
${your_own_workspace}/fimtyper /src/fimtyper.sh s3://fas_file_uri
AWS S3 + AWS ECS + AWS BATCH
- In the src directory create /src/fimtyper.sh, it must include a call to the /usr/local/fimtyper/fimtyper.pl tool and the input directory linked with AWS S3. You can place the S3 configuration and the parameters for the FimTyper tool in /conf folder.
- Push the image to your AWS Account (AWS ECR)
- Create an AWS BATCH job that points to the FimTyper image, previously uploaded in AWS ECR.
In this implementation, we just pointed to the core aspect. Be aware that a first glance, you will need to configure AWS services like AWS Networking, AWS IAM, AWS S3, AWS Batch
ref: