Basic Bioinformatics Docker Package

A docker package that provides basic bioinformatics tools in an Ubuntu Linux environment that can be used on any other OS that supports Docker (specifically Mac OS and Windows). To download and install Docker, please visit their website - https://docs.docker.com/get-docker/

This is intended to be a starting point for a potentially shareable common Linux environment where basic bioinformatics analysis tasks may be performed on small or medium sized examples or data sets. It was initially created for attendees of a workshop for bioinformatics, but may be generally useful for others wanting a Linux environment to work with from other operating systems and platforms.

Getting Started

Downloading this Package (One-Time Only)

From a suitable folder on your Host Machine, run

git clone https://github.com/cheelee/basic_bioinformatics.git

Initialize the Package (One-Time Only)

MacOS

1. Start Docker.
2. [Optional] Review and edit the Dockerfile accordingly.
3. [Optional] Modify macos_build_image.sh if you wish to change the default user name, and location information.
4. [Optional] Modify macos_init_container.sh to use the same user name if you had modified it in the previous step.
5. Open a Terminal, and go to the folder for this package.
6. Build the Docker image - Run macos_build_image.sh
7. Initialize the Docker container - Run macos_init_container.sh.

Windows

1. Start Docker.
2. [Optional] Review and edit the Dockerfile accordingly.
3. [Optional] Modify windows_build_image.bat if you wish to change the default user name, and location information.
4. [Optional] Modify windows_init_container.bat to use the same user name if you had modified it in the previous step.
5. Build the Docker image - Double-click on windows_build_image.bat.
6. Initialize the Docker container - Double-click on windows_init_container.bat.

Starting the Bioinformatics Image Environment

MacOS

1. Start Docker.
2. Ensure that the Docker container (name: "bioinformatics") is running via the Docker Dashboard.
3. Open a Terminal, and run the line written inside. If you had changed the user name when building the image, remember to also use the changed name - Run docker exec --user default_user -it bioinformatics bash
4. Your Terminal window will not change, but you are now working inside the Ubuntu image.

Windows

1. Start Docker.
2. Ensure that the Docker container (name: "bioinformatics") is running via the Docker Dashboard.
3. Double-click on windows_start_terminal.bat. This will open a new terminal window, and it will be inside the Ubuntu image.

Usage

Tutorials

Simple tutorials are provided covering various stages of simple bioinformatics. Each tutorial is captured in the subfolders of ~/data/simple_tutorials as the file tutorial.sh. You can use the command cat tutorial.sh to view each of them. The tutorials use data from publicly available AMR tools, and NCBI Sars-Cov2 reads and reference sequences.

Sharing Data between the Ubuntu Docker image and Host Machine.

This applies to both MacOS and Windows. In the package are two folders share_in and share_out and their counterparts inside the Ubuntu image are external_share_in and external_share_out respectively.

From your Host Machine, you can modify files or drag-and-drop files into both folders. From inside the Ubuntu image, you are only allowed to read from external_share_in but you are allowed to write new files to external_share_out.

Access to External Data from the Ubuntu Docker image.

The Ubuntu image will have access to the Internet in the same way your Host Machine has. You may run tools and software like git, and wget from inside the image to access the internet environment like NCBI and Github.

Custom Personal Bioinformatics Workflows

You are free to use this package any way you see fit. You can copy your own sequence data into the share_in folder (it is read-only, so nothing the image does will damage that data). You can also generate analysis results via the tools installed, and place it into the share_out for downstream GUI tools like Geneious. You can even choose to install or develop your own tools and Linux packages into your own images if you understand how to do so.

Tools, Bioinformatics topics, and concepts supported.

Basic Linux operations and tools.

It is beyond the scope of this package to cover all of standard Linux use. Please consult other tutorials and guides. The following are general categories of tasks that are supported in this package.

• Navigating the Linux file and folder environment - tree, pwd, cd, ls.
• Modifying the Linux folder environment - mkdir, rmdir, mv.
• Modifying Linux files - cp, rm, mv.
• Viewing the content of text files - cat, head, tail.
• Finding content lines in text files - grep.
• Content manipulation and data extraction - cut, tr, sort, uniq.
• Working with shared repositories - git.

Common bioinformatics workflows.

• Review and manipulation of sequence data files (fasta, fastq) - seqtk.
• Downloading data (reference sequences, genbank, etc) - efetch. Unfortunately there are currently problems getting efetch to install cleanly, and this package is not provided here.
• Evaluation of raw sequenced reads (fastq) - fastqc, multiqc.
• Simple taxonomic identification of reads - kraken2. No support for kraken2 is provided here because of the large sizes of databases required to allow it to work well.
• De novo assembly of raw sequenced reads into contigs - Trinity.
• Review the quality of assemblies - Quast. No support for Quast is provided in this package.
• Reference-based assembly and consensus of raw sequenced reads - multiple steps involving tools like bwa for Illumina reads, or minimap2 for Oxford nanpore reads. Beyond the scope of this package.
• Simple local alignment - water (emboss).
• Simple global alignment - needle, stretcher (emboss).
• Nucleotide sequence alignment and identification - blastn.
• Protein sequence alignment and identification - blastx, diamond.
• Mapping of sequenced reads to reference sequences - minimap2.
• Review of reads-to-reference coverage and depth information - samtools.
• Multiple alignment of sequences of similar length - mafft.
• Phylogenetic tree building - raxmlHPC.
• Automation - python3. No guide is provided here. Seek tutorials on python online as the use cases are very varied.
• Variant Calling/Analysis - vcftools,bcftools,vt. vt is not provided in this package but is currently available on Github at https://github.com/atks/vt