RNA-seq pipeline as described in Wang et al 2016 PMID:26483013
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A Linux-based Docker container with all the software for all command line exercises described in:
Using RNA-seq for Analysis of Differential Gene Expression in Fungal Species. Wang C, Schröder MS, Hammel S, Butler G. Methods Mol Biol. 2016;1361:1-40. doi: 10.1007/978-1-4939-3079-1_1. PMID: 26483013 https://www.ncbi.nlm.nih.gov/pubmed/26483013
Complete Linux-based container for all command line processing as directed in Wang et al 2016 (PMID: 26483013)
Includes:
Specific versions and sources are made clear in the Dockerfile.
See here and here for additional information related to versions.
As far as I know, the only requirement is a working installation of Docker on your machine where you want to work. If that is not possible on your local computer, you could always access a Linux-based instance from your local computer.
You'll need two things:
a running Docker container derived from this image with all necessary software already set up
the data to perform the anlaysis on
Get the container based on the image running.
(Because the data files are large, you may want to at least start that download at this point. See below. While that is downloading, you can also be setting up the Docker container.)
If you haven't already, make a directory called data on local machine upon which you'll be running Docker. This is a directory where you'll place your data. Make a note of the path. For example, on my Mac I made it with the path /Users/Wayne/data. You can use your graphical OS or a command line to make the local directory. Doesn't matter how as long as you make one to serve as where you link the data directory within your container by binding a volume.
Then in your terminal issue the command to get and run the container
docker run -v /Users/Wayne/data:/data -it fomightez/rnaseqwang
, where you replace /Users/Wayne/data part with the full path of your local data directory.
After that gets the image and kicks off running it. you'll then end up with a command line prompt that looks sort of like this
root@e84005c430c8:/data#
The e84005c430c8 string will be something else, but this means your are actually in your Docker container ready to go.
Any time you need to get back to the command line of your local computer. You can just type exit to leave the container, but stay there for now.
If you type ls to list the files present in the current directory and see nothing, continue on to step #2. If you already have the data in your local data directory on your computer, you should see it in /data directory within your container.
Download the data.
Using your browser or another window of command line interface with the wget or curl command, download the supp_data.tar.gz file from http://cgob.ucd.ie/supp_data/supp_data.tar.gz .
If you get the data from there it will also have the output files generated by working through the steps in the Wang et al 2016 example analysis.
Alternatively, you can get just the raw data from the Short Read Archive (SRA). This is not the recommended route for this case and is an effort not for the faint hearted, but using the SRA and Gene Expression Omnibus (GEO) or European Nucleotide Archive (ENA) resources might be important to you later for getting public data. Our campus network makes the route using the SRA Toolkit difficult/impossible. Your mileage may vary. The individual reads are stored in the SRA under accession number SRP041812. The dataset is under the GEO accession number GSE57451. Adapt the information here to suit this data set. You can disregard the information about where to work though, and you may wish to look at the information earlier on that page too.
For ease in referencing the locale, I suggest keeping the data in a folder called data on your system and these steps assume you did that. Feel free to deviate and adapt the commands to match where you have placed the data.
Make a directory called data on local machine upon which you'll be running Docker. This is a directory where you'll place your data. Make a note of the path. For example, on my Mac I made it with the path /Users/Wayne/data. You can use your graphical OS or a command line to make the local directory. Doesn't matter how as long as you make one to serve as where you link the data directory within your container by binding a volume.
However you aquire the data, move it into that folder. If you obtained the data as the supp_data.tar.gz file you'll need to unpack it. Because it contains all the output files generated as well. I suggest sticking in with a directory called dl within the data directory. Move the raw reads back out to data` with the following commands
PUT COMMANDS TO DO THAT HERE
If you have your Docker container running in a terminal window, switch to it. If you exited, start it back up with
docker run -v /Users/Wayne/data:/data -it fomightez/rnaseqwang
again. Assuming you already did step #1, it will be instantaneous to restart because it has all the needed information on your local system already.
Remember any time you need to get back to the command line of your local computer. You can just type exit to leave the container, and you can always restart the Docker container with
docker run -v /Users/Wayne/data:/data -it fomightez/rnaseqwang
You'll need a running contianer to continue on.
If for some reason you wanted Docker to use the Dockerfile to build locally, the command is
docker build -t YOURchoiceOFname .
, where YOURchoiceOFname part gets replaced with what you'd like to call.
It is easier to just get the already built image from Docker hub though, see the Usage section.
Content type
Image
Digest
Size
925.9 MB
Last updated
over 9 years ago
docker pull fomightez/rnaseqwang