Editing Nanopore RNA Sequencing Protocol (section)

=====Pre-requisites=====

''EpiNano'', unfortunately, relies upon a series of tools and software packages, both inside and outside of ''R''. Therefore, we will need to check to ensure all of these are installed prior to getting ''EpiNano'', and install any that we do not have using either ''Conda'' or <code>install.packages()</code> (depending on the package). Many of the packages required are older versions of those commonly used, but some of the newer versions do work with ''EpiNano''. Therefore, I am going to make a ''Conda'' environment that is designed to be used specifically for ''EpiNano'', and then switch to that environment prior to the install. That way, we can install the older packages within an ''EpiNano'' “specific” environment that can be loaded and used separately from our base ''Conda'' environment.

<code>Bash</code>
<syntaxhighlight lang="Bash">
conda create --name epinano
conda activate --stack epinano
</syntaxhighlight>

The text in parentheses next to your name in ''Terminal'' should now swap to <code>(epinano)</code>. To return to your base, simply type <code>conda activate --stack base</code> and execute.

Note that at any time, you can see a list of installed ''Conda'' packages along with their versions via the following command:

<code>Bash</code>
<syntaxhighlight lang="Bash">
conda list
</syntaxhighlight>

If you just made a new stack named <code>epinano</code>, it should be empty. Let’s go ahead and now start installing packages. I like to start with <code>scikit-learn</code>, since it will install a lot of the correct dependencies for the other packages. To install the right version, add a double equals sign after the name to specify the version number, such as <code>conda install scikit-learn==0.20.2</code>. It may take a while to find the package this way.

{{warning|''EpiNano'' 1.2 does '''NOT''' work with the latest versions of python, scikit-learn, etc. Therefore, you will want to install the version of each package as you see here, which can be done with <code>conda install package</code>. As packages install, pay attention to which packages might be upgraded or downgraded as you go along. If you do not, you might run into errors when trying to run ''EpiNano'' scripts if a package was changed without your knowledge!}}

{| class="wikitable"
|+EpiNano Conda Packages
|-
! scope="col"| Package
! scope="col"| Version
! scope="col"| Notes
|-
|biopython
|1.76
|
|-
|dask
|2.5.2
|
|-
|h5py
|2.8.0
|
|-
|java openjdk
|1.8.0
|This should already be installed via a previous step.
|-
|minimap2
|2.14-r886
|This should already be installed via a previous step.
|-
|nanopolish
|0.12.4
|
|-
|numpy
|1.15.4
|
|-
|pandas
|0.23.4
|
|-
|pysam
|0.15.3+
|
|-
|python
|3.6.7
|<b>Note:</b> Latest version of python doesn't work with scikit-learn 0.20.2!
|-
|sam2tsv
|
|Included with the EpiNano repo at <code>EpiNano/misc/</code>.
|-
|samtools
|0.1.19
|This should already be installed via a previous step.
|-
|scikit-learn
|0.20.2
|<b>Note:</b> <code>Epinano_Predict.py</code> does not work with the latest version. You ''must'' install this one for EpiNano.
|}

Now let’s check the ''R'' packages. Boot up ''R'' in the terminal by typing <code>R</code>, and execute the following in the console to generate a list of the currently installed packages. If you do not have R, you can install it [https://anaconda.org/r/r using Conda], or following the instructions provided [https://www.r-project.org/ here].

<code>R</code>
<syntaxhighlight lang="R">
as.data.frame(installed.packages()[ , c(1, 3:4)])
</syntaxhighlight>

Cross reference the list that prints with the following (again, sorted in alphabetical order here for you), and install any ''R'' packages that you do not have using the <code>install.packages()</code> command. I recommend starting with the car package, since it will install a lot of the others in the list automatically for you. I also didn’t have an issue installing the latest packages of each listed here, so you likely don’t need to install a specific version for ''EpiNano'' to run.

{{warning|Some of these packages may have issues installing on ''Linux'' if certain commands are unavailable to ''R''. For example, you may need to also install <code>curl</code> or <code>gfortran</code> in order to get the packages <code>tidyverse</code> and <code>car</code> to install. Pay attention to the output in the console and read the directions for the next steps if any fail (which will be apparent to you if you see the line <code>Installation of package had non-zero exit status</code> printed anywhere). After all the installations are done, you should recheck the list of installed packages again (see note following the table below).}}

{| class="wikitable"
|+EpiNano R Packages
|-
! scope="col"| R Package
! scope="col"| Version
! scope="col"| Notes
|-
|car
|3.0-3
|
|-
|dplyr
|1.0.1
|
|-
|forcats
|0.4.0
|
|-
|ggplot2
|3.1.1
|
|-
|ggrepel
|0.8.1
|
|-
|optparse
|1.6.6
|
|-
|outliers
|0.14
|
|-
|purrr
|0.3.2
|
|-
|readr
|1.3.1
|
|-
|reshape2
|1.4.3
|
|-
|stringr
|1.4.0
|
|-
|tibble
|3.0.3
|
|-
|tidyr
|0.8.3
|
|-
|tidyverse
|1.2.1
|
|}

You should check that these actually installed after finishing by executing the <code>as.data.frame(installed.packages()[ , c(1, 3:4)])</code> command once again.