Using conda environments¶
Let's get started with conda!
To follow along with this lesson, we are using a binder with an Rstudio interface. Binders use collections of files from Github repositories with instructions on software installation to create small (and free!) computing environments. They are used for teaching and demonstrating software functionality or analysis workflows.
Open the binder for this lesson in a new tab (i.e., by typing Ctrl and clicking link): Click me to launch binder!
It may take 3-4 minutes for the binder to load!
For this lesson, we are using Rstudio to teach you conda because it consolidates showing the conda commands, terminal, and file system all on 1 screen. In practice, you can use conda through a command-line terminal interface without Rstudio.
We are using 3 of the Rstudio panels for this lesson: Source panel to run conda commands, Terminal panel to execute code, and File panel to view input/output files. You can rearrange the panels to help with viewing:
What happens if I get a 502, 503, or 504 error from the binder?
Try clicking on the launch button again to re-launch. The binder or internet connection may have timed out.
Conda is already installed in the binder so the next step is to set it up. We'll talk more about setting conda up on your local system later in the lesson!
To follow along, copy/paste commands into the terminal OR run the commands from the "workshop_commands.sh" file in the binder (in File Rstudio panel). Either click Run or type Cmd+Enter on Macs and Ctrl+Enter on Windows computers.
The conda installer sets up two things: Conda and the base environment (also called "root"). The base environment contains a version of python (specified during installation) and some basic packages. As illustrated below, you can then create additional environments with their own software installations, including other versions of the same software (i.e., python 3 in base environment and python 2.7 in a separate environment).
Image credit: Gergely Szerovay
Setup the conda installer and initialize the settings:
The binder auto-generates a very long command prompt. We will shorten it to
echo "PS1='\w $ '" >> .bashrc
Re-start terminal for the changes to take effect (type
exit and then open a new terminal).
We are currently in the
(base) conda environment.
Conda channels: Searching for software¶
The channels are places where conda looks for packages. The default channel after conda installation is set to Anaconda Inc's channels (Conda's Developer).
conda config --show channels conda list # get list of packages in base environment
You might notice that our installation of conda on the binder already had the
conda-forge channels. This is due to the binder's set up. But in practice on your own system, it's important to add the channels as shown in this lesson.
Channels exist in a hierarchical order. By default, conda searches for packages based on:
Channel priority > package version > package build number
Image credit: Gergely Szerovay
Commonly used channels:
- In the absence of other channels, conda searches the
biocondaare channels that contain community-contributed software
Biocondaspecializes in bioinformatics software
Biocondasupports only 64-bit Linux and Mac OS
- package list
conda-forgecontains many dependency packages
- You can even install R packages with conda!
We will update the channel list order and add
bioconda since we are using bioinformatics tools today. The order of the channels matters!
First, add the
defaults channel with the
conda config --add channels command. We can check the channel priority order with the
conda config --get channels command.
conda config --add channels defaults conda config --get channels
Then add the
conda config --add channels bioconda conda config --get channels
Lastly, add the
conda-forge channel to move it to top of the list, following Bioconda's recommended channel order. This is because many packages on
bioconda rely on dependencies that are available on
conda-forge, so we want conda to search for those dependencies before trying to install any bioinformatics software.
conda config --add channels conda-forge conda config --get channels
With this configuration, conda will search for packages first in
bioconda, and then
Another way to add channels is:
conda config --prepend channels bioconda
Install Software and Create Environments¶
For our demo, we need to install FastQC, a commonly used software tool that provides quality control reports for raw sequencing data.
Search for software (fastqc):
conda search fastqc
It may take a few seconds for the software list to display. The table shows all the versions and builds of fastqc available for installation with conda. They are all stored in the bioconda channel.
Loading channels: done # Name Version Build Channel fastqc 0.10.1 0 bioconda fastqc 0.10.1 1 bioconda fastqc 0.11.2 1 bioconda fastqc 0.11.2 pl5.22.0_0 bioconda fastqc 0.11.3 0 bioconda fastqc 0.11.3 1 bioconda fastqc 0.11.4 0 bioconda fastqc 0.11.4 1 bioconda fastqc 0.11.4 2 bioconda fastqc 0.11.5 1 bioconda fastqc 0.11.5 4 bioconda fastqc 0.11.5 pl5.22.0_2 bioconda fastqc 0.11.5 pl5.22.0_3 bioconda fastqc 0.11.6 2 bioconda fastqc 0.11.6 pl5.22.0_0 bioconda fastqc 0.11.6 pl5.22.0_1 bioconda fastqc 0.11.7 4 bioconda fastqc 0.11.7 5 bioconda fastqc 0.11.7 6 bioconda fastqc 0.11.7 pl5.22.0_0 bioconda fastqc 0.11.7 pl5.22.0_2 bioconda fastqc 0.11.8 0 bioconda fastqc 0.11.8 1 bioconda fastqc 0.11.8 2 bioconda fastqc 0.11.9 0 bioconda
Now, let's create a conda environment with fastqc installed in it.
Create conda environment and install FastQC. This takes a few minutes (you'll see the message "Solving environment").
-y flag tells conda not to ask you for confirmation about downloading software. The
-n) flag specifies the environment's name. The last element of the command,
fastqc, specifies the software package to install.
conda create -y --name fqc fastqc
More options to customize the environment are documented under the help page for this command:
conda create -h.
The software you installed will only be available to use after you activate the environment:
conda activate fqc
This command shows you information about the activated conda environment:
One way to make sure the software works is to check the version:
To go back to
(base) ~ $ environment:
High-throughput sequencing data quality control steps often involve FastQC and Trimmomatic. Trimmomatic is useful for read trimming (i.e., adapters). There are multiple ways we could create a conda environment that contains both software programs:
Method 1: install software in existing environment¶
We could add
trimmomatic to the
conda install -y trimmomatic=0.36 conda list # check installed software
We can specify the exact software version with
= and a version number. The default is to install the latest version, but sometimes your workflow may depend on an older version.
Software can also be installed by specifying the channel with
conda install -c conda-forge -c bioconda trimmomatic=0.36
or if needed, by specifying version and build (the default is to install the latest version and build):
conda install trimmomatic=0.32=0
When you switch conda environments, conda changes the file path (and other environment variables) to searches for software packages in different folders.
Let's check the PATH for method 1:
You should see that the first element (
/srv/conda/envs/fqc/bin:) in the file path changes each time you switch environments!
Method 2: install both software during environment creation¶
For this method, we list
fastqc to create an environment with both installed, all with 1 command. Like above, remember to activate the environment and then you can check the list of packages to verify installation and check the PATH to verify that conda switched to the
conda deactivate conda create -y --name fqc_trim fastqc trimmomatic=0.36 conda activate fqc_trim # check installed software conda list # path for method 2 echo $PATH
The following methods use an external file to specify the packages to install:
Method 3: specify software to install with a YAML file¶
Often, it's easier to create environments and install software using a YAML file that specifies all the software to be installed. For our example, we are using a file called
Let's start back in the
test.yml file contains the following in YAML format:
name: qc_yaml #this specifies environment name channels: - conda-forge - bioconda - defaults dependencies: - fastqc - trimmomatic=0.36
YAML is a file format that is easy for both computers and humans to read. The YAML file extension is
.yml and these files can be generated in any text editor.
For conda, the
name: is optional (it can also be specified in the
conda env create command), but it must have a list of
channels: and a list of
dependencies:. Notice that the channels are list with highest to lowest priority.
Create the environment - note the difference in conda syntax. This method uses the
conda env create command instead of
conda create. The
--file) flag specifies the file with the channels and software to set up.
# since environment name specified in yml file, we do not need to use -n flag here conda env create -f test.yml conda activate qc_yaml # check installed software conda list
Method 4: Install exact environment¶
For this approach, we export a list of the exact software package versions installed in a given environment and use it to set up new environments. This set up method won't necessarily install the latest version of a given program, but it will replicate the exact environment set up you exported from.
conda activate fqc conda list --export > packages.txt conda deactivate
Two options -
1) install the exact package list into an existing environment:
conda install --file=packages.txt
2) set up a new environment with the exact package list:
conda env create --name qc_file -f packages.txt
At this point, we have several conda environments! To see a list:
conda env list
The current environment you're in is marked with an asterisk
There are a few redundant commands in conda. For example, this command does exactly the same thing as the one above:
conda info --envs
Generally, you want to avoid installing too many software packages in one environment. The more software you install, the longer it takes for conda to resolve compatible software versions for an environment (it'll take longer and longer at the "Solving environment" stage).
For this reason, and in practice, people often manage software for their workflows with multiple conda environments.
Running FastQC in a conda environment¶
Let's run a small analysis with FastQC in the
fqc environment we created above.
If not already done, activate one of the environments we created, e.g.,:
conda activate fqc
Let's make sure the software was installed correctly by looking at the help documentation:
Output should look like:
FastQC - A high throughput sequence QC analysis tool SYNOPSIS fastqc seqfile1 seqfile2 .. seqfileN fastqc [-o output dir] [--(no)extract] [-f fastq|bam|sam] [-c contaminant file] seqfile1 .. seqfileN ...
Download data (a yeast sequence file):
curl -L https://osf.io/5daup/download -o ERR458493.fastq.gz
Check out the data:
gunzip -c command allows us to see the unzipped version of the file without actually unzipping it (you can verify this by checking the file extension after running this command!). The
| is called a pipe and it takes the output of the
gunzip -c command and hands it to the
wc word count command. The
-l flag tells
wc we want to count the number of lines in the file.
gunzip -c ERR458493.fastq.gz | wc -l
There should be 4,375,828 lines in the file.
What does the fastq file look like?
Here are two ways to look at the sequence read file:
1. Use the
gunzip -c and pipe the output to the
head command to show the first 10 lines of the file:
gunzip -c ERR458493.fastq.gz | head
2. Use the
less command to scroll through the file:
The beginning of the fastq format sequence file should look like this, where the 1st line is the sequence read ID (starts with
@), the 2nd line is the DNA sequence, the 3rd is sequence separator
+, and the 4th is the Phred quality score associated with each base pair in ASCII format.
@ERR458493.1 DHKW5DQ1:219:D0PT7ACXX:1:1101:1724:2080/1 CGCAAGACAAGGCCCAAACGAGAGATTGAGCCCAATCGGCAGTGTAGTGAA + B@@FFFFFHHHGHJJJJJJIJJGIGIIIGI9DGGIIIEIGIIFHHGGHJIB @ERR458493.2 DHKW5DQ1:219:D0PT7ACXX:1:1101:2179:2231/1 ACTAATCATCAACAAAACAATGCAATTCAAGACCATCGTCGCTGCCTTCGC + B@=DDFFFHHHHHJJJJIJJJJJJIJJJJJJJJJJJJJJJJJJJJIJJJJI @ERR458493.3 DHKW5DQ1:219:D0PT7ACXX:1:1101:2428:2116/1 CTCAAAACGCCTACTTGAAGGCTTCTGGTGCTTTCACCGGTGAAAACTCCG ...
If you used the
less command, type Q to exit the page.
On the terminal screen, FastQC prints analysis progress:
Started analysis of ERR458493.fastq.gz Approx 5% complete for ERR458493.fastq.gz Approx 10% complete for ERR458493.fastq.gz Approx 15% complete for ERR458493.fastq.gz Approx 20% complete for ERR458493.fastq.gz Approx 25% complete for ERR458493.fastq.gz Approx 30% complete for ERR458493.fastq.gz Approx 35% complete for ERR458493.fastq.gz ... Analysis complete for ERR458493.fastq.gz
The final output file is called "ERR458493_fastqc.html".
You can click on the
.html file in the File panel to open it in a web browser. This is the quality check report for our yeast sequence file.