Merge pull request #14 from TRON-Bioinformatics/release_1.3.6

Release 1.3.6

Docker/Dockerfile

@@ -3,14 +3,16 @@ from ubuntu:20.04
 RUN apt-get update -y --fix-missing
 RUN DEBIAN_FRONTEND="noninteractive" apt-get install -y software-properties-common git python python3 python3-pip emacs curl wget zip unzip tar zlib1g-dev liblzo2-dev libcurl4-openssl-dev libssl-dev libncurses5 tzdata
 
+COPY ./code/ /code/
+
 RUN curl -O https://repo.anaconda.com/miniconda/Miniconda2-latest-Linux-x86_64.sh
-RUN bash Miniconda2-latest-Linux-x86_64.sh -b -p /root/miniconda2
+RUN bash Miniconda2-latest-Linux-x86_64.sh -b -p /code/miniconda2
 RUN rm Miniconda2-latest-Linux-x86_64.sh
-ENV PATH /root/miniconda2/bin:$PATH
+ENV PATH /code/miniconda2/bin:$PATH
 RUN conda update conda
 RUN conda update --all
-RUN conda install -y -c anaconda pandas=0.24.0 biopython=1.73
-RUN conda install -y -c conda-forge python-lzo=1.12 python-xxhash=1.4.3
+RUN conda install -y -c anaconda pandas=0.24.0
+RUN conda install -y -c conda-forge python-lzo=1.12 python-xxhash=1.4.3 biopython=1.73
 RUN conda install -y -c bioconda pysam=0.15.2 star=2.6.1b samtools=1.9.0 mapsplice=2.2.1
 RUN conda install -y -c bioconda star-fusion=1.5.0 bowtie=1.1.2
 RUN conda install -y -c bioconda bowtie2=2.3.4.3
@@ -26,6 +28,7 @@ RUN wget -qO- https://cloud.r-project.org/bin/linux/ubuntu/marutter_pubkey.asc |
 RUN add-apt-repository "deb https://cloud.r-project.org/bin/linux/ubuntu $(lsb_release -cs)-cran40/"
 RUN apt-get install -y r-base
 
+ENV PERL5LIB "$PERL5LIB:/code/SOAPfuse/1.27/source/bin/perl_module/"
 
 # Install R packages
 
@@ -35,15 +38,12 @@ RUN R --slave -e 'remotes::install_version("tidyverse", "1.2.1")'
 RUN R --slave -e 'remotes::install_version("XML", "3.99-0.9")'
 RUN R --slave -e 'remotes::install_version("randomForest", "4.6-14")'
 
-COPY ./code/ /code/
-
-# After release 1.3.5 these lines can be used to automate docker image creation process further
-#RUN wget https://github.com/TRON-Bioinformatics/EasyFuse/archive/refs/tags/v1.3.5.tar.gz && \
-#tar xvfz v1.3.5.tar.gz && \
-#mv EasyFuse-1.3.5/ /code/easyfuse/ && \
-#cd /code/easyfuse/ && \
-#mv config.ini.docker config.ini && \
-#mv build_env.sh.sample build_env.sh && \
-#mv blacklist.txt.sample blacklist.txt
 
-ENV PERL5LIB "$PERL5LIB:/code/SOAPfuse/1.27/source/bin/perl_module/"
+# After release 1.3.6 these lines can be used to automate docker image creation process further
+# RUN rm -rf /code/easyfuse/ && \
+# git clone -b  release_1.3.6 https://github.com/TRON-Bioinformatics/EasyFuse.git && \
+# mv EasyFuse /code/easyfuse && \
+# chmod -R a+rx /code && \
+# mv /code/easyfuse/config.ini.docker /code/easyfuse/config.ini && \
+# mv /code/easyfuse/build_env.sh.sample /code/easyfuse/build_env.sh && \
+# mv /code/easyfuse/blacklist.txt.sample /code/easyfuse/blacklist.txt && \

Docker/build_docker.sh

@@ -0,0 +1,12 @@
+#!/bin/bash
+
+# Specify image tag, e.g. `docker.io/tronbioinformatics/easyfuse:latest`
+IMAGE_TAG=$1
+
+# Specify path containing Dockerfile and context
+PATH=$2
+
+docker build \
+--rm \
+-t ${IMAGE_TAG} \
+${PATH}

Docker/convert_docker_to_singularity.sh

@@ -0,0 +1,13 @@
+#!/bin/bash
+
+# Specify image ID from `docker images`
+IMAGE_ID=$1
+
+# Specify output folder to store files
+OUTPUT_DIR=$2
+
+# Save Docker image to .tar archive
+docker save <image_id> -o ${OUTPUT_DIR}/easyfuse_latest.tar
+
+# Build Singularity image from .tar archive and save it to .sif file
+singularity build ${OUTPUT_DIR}/easyfuse_latest.sif docker-archive://${OUTPUT_DIR}/easyfuse_latest.tar

Docker/run_docker.sh

@@ -0,0 +1,22 @@
+#!/bin/bash
+
+
+# Specify path to reference folder,
+REFERENCE_FOLDER=$1
+
+# Specify path to data folder,
+DATA_FOLDER=$2
+
+# Specify image tag, e.g. `docker.io/tronbioinformatics/easyfuse:latest`
+IMAGE_TAG=$3
+
+# Specify output folder name, e.g. `results`
+OUTPUT_FOLDER_NAME=$4
+
+docker run \
+--name easyfuse_container \
+-v ${REFERENCE_FOLDER}:/ref \
+-v ${DATA_FOLDER}:/data \
+--rm \
+-it ${IMAGE_TAG} \
+python /code/easyfuse/processing.py -i /data/input_fastqs -o /data/${OUTPUT_FOLDER}/

Docker/run_docker_interactive.sh

@@ -0,0 +1,14 @@
+#!/bin/bash
+
+# Specify path to reference folder,
+REFERENCE_FOLDER=$1
+
+# Specify image tag, e.g. `docker.io/tronbioinformatics/easyfuse:latest`
+IMAGE_TAG=$2
+
+
+docker run \
+--name easyfuse_container \
+-v ${REFERENCE_FOLDER}:/ref \
+-it ${IMAGE_TAG} \
+/bin/bash

Docker/run_singularity.sh

@@ -0,0 +1,22 @@
+#!/bin/bash
+
+
+# Specify path to reference folder,
+REFERENCE_FOLDER=$1
+
+# Specify path to data folder,
+DATA_FOLDER=$2
+
+# Specify image tag or SIF, e.g. `docker://docker.io/tronbioinformatics/easyfuse:latest`
+DOCKERHUB_OR_SIF=$3
+
+# Specify output folder name, e.g. `results`
+OUTPUT_FOLDER_NAME=$4
+
+
+singularity exec \
+--containall \
+--bind ${REFERENCE_FOLDER}:/ref \
+--bind ${DATA_FOLDER}:/data \
+${DOCKERHUB_OR_SIF} \
+python /code/easyfuse/processing.py -i /data/input_fastqs -o /data/${OUTPUT_FOLDER_NAME}/

README.md

@@ -1,28 +1,21 @@
 # EasyFuse 
 
-![GitHub release (latest SemVer)](https://img.shields.io/github/v/release/tron-bioinformatics/EasyFuse)
-![Docker Image Version (latest semver)](https://img.shields.io/docker/v/tronbioinformatics/easyfuse?label=docker)
+[![GitHub release (latest SemVer)](https://img.shields.io/github/v/release/tron-bioinformatics/EasyFuse)](https://github.com/TRON-Bioinformatics/EasyFuse/releases)
+[![Docker Image Version (latest semver)](https://img.shields.io/docker/v/tronbioinformatics/easyfuse?label=docker)](https://hub.docker.com/r/tronbioinformatics/easyfuse)
 [![License](https://img.shields.io/badge/license-GPLv3-green)](https://opensource.org/licenses/GPL-3.0)
 
 EasyFuse is a pipeline to detect fusion transcripts from RNA-seq data with high accuracy.
 EasyFuse uses five fusion gene detection tools, [STAR-Fusion](https://github.com/STAR-Fusion/STAR-Fusion/wiki), [InFusion](https://bitbucket.org/kokonech/infusion/src/master/), [MapSplice2](http://www.netlab.uky.edu/p/bioinfo/MapSplice2), [Fusioncatcher](https://github.com/ndaniel/fusioncatcher), and [SoapFuse](https://sourceforge.net/p/soapfuse/wiki/Home/) along with a powerful read filtering strategy, stringent re-quantification of supporting reads and machine learning for highly accurate predictions.
 
 <p align="center"><img src="img/easyfuse_workflow.png"></p>
 
-- Documentation: [EasyFuse Wiki](https://github.com/TRON-Bioinformatics/EasyFuse/wiki)
-- Paper: https://doi.org/10.1038/s41587-022-01247-9
+ - Documentation: [EasyFuse Wiki](https://github.com/TRON-Bioinformatics/EasyFuse/wiki)
+ - Publication: [Weber D, Ibn-Salem J, Sorn P, et al. Nat Biotechnol. 2022](https://doi.org/10.1038/s41587-022-01247-9)
 
-We recommend using EasyFuse with the Docker container.
+We recommend using EasyFuse with Docker or Singularity.
 
-## Usage with Docker
+## Usage
 
-### Download the image
-
-The Docker image can be downloaded from [dockerhub](https://hub.docker.com/r/tronbioinformatics/easyfuse) using the following command:
-
-```
-docker pull tronbioinformatics/easyfuse:latest
-```
 
 ### Download reference data
 
@@ -40,15 +33,24 @@ md5sum -c easyfuse_ref_v2.tar.gz.md5 easyfuse_ref_v2.tar.gz
 tar xvfz easyfuse_ref_v2.tar.gz
 ```
 
-### Run EasyFuse
+### Run EasyFuse with Docker
+
+The Docker image can be downloaded from [dockerhub](https://hub.docker.com/r/tronbioinformatics/easyfuse) using the following command:
+
+```
+docker pull tronbioinformatics/easyfuse:latest
+```
 
 EasyFuse will require three folders:
-* The input data folder containing FASTQ files, in this example `/path/to/input_data`.
+
+* The input data folder containing FASTQ files, in this example `/path/to/data`.
 * The reference data folder, in this example `/path/to/easyfuse_ref`
 * The output folder, in this example `/path/to/output`
 
 Now EasyFuse can be started by mapping the input data, references and output folders.
 
+Using Docker:
+
 ```
 docker run \
   --name easyfuse_container \
@@ -58,10 +60,23 @@ docker run \
   --rm \
   -it easyfuse:latest \
   python /code/easyfuse/processing.py -i /data -o /output
+
 ```
 
+### Run EasyFuse with Singularity
+
+```
+singularity exec 
+  --containall \
+  --bind </path/to/easyfuse_ref>:/ref \
+  --bind </path/to/data>:/data \
+  --bind </path/to/output>:/output \  
+  docker://tronbioinformatics/easyfuse:latest \
+  python /code/easyfuse/processing.py -i /data/ -o /output
+
+```
 
-The output can be found in `</path/to/output>/results/`. The Output format is described in the wiki page [EasyFuse Output](https://github.com/TRON-Bioinformatics/EasyFuse/wiki/EasyFuse-Output)
+The output can be found in `</path/to/output>/FusionSummary`. The Output format is described in the wiki page [EasyFuse Output](https://github.com/TRON-Bioinformatics/EasyFuse/wiki/EasyFuse-Output)
 
 ## Custom Installation
 

config.ini.docker

@@ -5,7 +5,7 @@
 # 4) To whom shall slurm mails be sent to (receiver)
 
 [general]
-version = 1.3.5
+version = 1.3.6
 pipeline_name = EasyFuse
 tools = QC,Readfilter,Fusioncatcher,Star,Starfusion,Infusion,Mapsplice,Soapfuse,Fetchdata,Summary
 fusiontools = Fusioncatcher,Starfusion,Infusion,Mapsplice,Soapfuse

config.ini.sample

@@ -5,7 +5,7 @@
 # 4) To whom shall slurm mails be sent to (receiver)
 
 [general]
-version = 1.3.5
+version = 1.3.6
 pipeline_name = EasyFuse
 tools = QC,Readfilter,Fusioncatcher,Star,Starfusion,Infusion,Mapsplice,Soapfuse,Fetchdata,Summary
 fusiontools = Fusioncatcher,Starfusion,Infusion,Mapsplice,Soapfuse