Hello! Today we'll be going through some hands-on activities to help you get familiar with the steps involved in genome assembly and quality assessment.

The first thing you should do if you haven't done so is connect to the ConGen server. We'll be working exclusively in the RStudio browser interface that you should be familiar with by now, but if you have questions or problems at any point please feel free to ask! Just in case, here's a annotated picture of roughly what you should be seeing right now. If you are seeing something drastically different or something that you don't understand, let us know.

Figure 1.1: The RStudio interface for running commands and browsing files.

Most of our work will be done as bash commands typed in the Terminal provided by RStudio. Throughout this walkthrough, commands will be presented as follows:

this is an example command

Following each command will be a table that goes through and explains each part of the command explicitly:

The goal of providing these tables is to break-down some of the 'black box' that command line tools can sometimes feel like. Hopefully this is helpful. If not, feel free to skip over these tables when you see them!

Commands that you should run will have a green background. We will also provide some commands that are beneficial to see, but do not necessarily need to be run using a red background, like so:

this is an example command that won't be run

Additionally, one of the most important and often overlooked parts of bioinformatics analyses is to simply look at ones data. There will be several points where we stop to look at the output of a given program or command. When we do, a snippet of the output will be presented in the walkthrough as follows:

Here is some made up output.
Looking at your data is very important!
You can catch problems before you use the data in later analyses.

Today we'll be talking about genome assembly. While the programs that perform the various steps of assembly have greatly improved over the past few years, genome assembly is still generally a slow, multi-step process. Given that, we'll be working with a smaller 150Mb genome from Drosophila pseudoobscura. Many times we will limit our data to just chromosome 2 (32Mb) of D. pseudoobscura to speed up run times even more.

D. pseudoobscura is a species of fruit fly that diverged from the well known D. melanogaster model species roughly 50 million years ago. D. pseudoobscura chromosome 2 is homologous to D. melanogaster chromosome arm 3R.

Figure 1.2: Drosophila phylogeny and homology between chromosome arms. From Schaeffer et al. 2008

Using these data, we'll be performing the following tasks today:

1. Assembling the D. pseudoobscura genome and assessing the quality of said assembly.
2. Mapping reads from D. pseudoobscura chromosome 2 to D. melanogaster chromosome 3R.
3. Assessing how iterative mapping of reads from D. pseudoobscura chromosome 2 to D. melanogaster affects divergence estimates.

Copying input data

The data we'll be working with today are mainly sequences in FASTA and FASTQ format (more on those in a moment). The input files are located on the server at ~/instructor_materials/Gregg_Thomas/congen-assembly/. Let's make a copy of this directory in our home directory so we don't have to worry about that path anymore. First, make sure you are in your home directory:

cd ~

Now let's make a copy of the data directory:

cp -r instructor_materials/Gregg_Thomas/congen-assembly/ .

Let's move into this folder with cd again since we'll spend the rest of the workshop here:

cd congen-assembly

And now we can look at what is in that folder with the ls command. Make sure you've selected your Terminal window and type the following:

ls

You should see the following folders listed

Preparing output directories

I like to try and think ahead about what outputs my project will produce and make those directories early on, which helps me plan out my workflows. Today we'll be generating assemblies, read mappings, and alignments, so let's prepare an output directory for each of those tasks.

mkdir alignments

mkdir assemblies

mkdir mapped-reads

We'll also be running the program FastQC, which requires a pre-made output directory:

mkdir fastqc-output

Some other programs we run will create their own output directories. We should now be ready to run the commands to generate assemblies and read mappings. But first, let's get familiar with our input data, sequences and reads...