Overview:

SAMtools is a suite of commands for dealing with databases of mapped reads. You'll be using it quite a bit throughout the course. It includes programs for performing variant calling (mpileup-bcftools). This tutorial expects you have already completed the Mapping tutorial.

Learning Objectives

1. Gain important insight into version control.
2. Familiarize yourself with SAMtools.
3. Use SAMtools to identify variants in the E. coli genomes we mapped in the previous tutorial.

Loading SAMtools – a lesson in version control

One of the most important aspects of science is that it is supposed to be reproducible, and as mentioned in an earlier tutorial, a computer will always do exactly what it is told... the trick is telling it to do what you actually want it to do. As bench scientists, we all know (or will soon learn) that protocols change slightly over time... maybe you have had the nightmare troubleshooting experience of a reliable protocol suddenly giving unreliable results only to find out that an enzyme/reagent/kit you bought from a different vendor because it was cheeper is actually not identical in every way, or maybe you find a kit or reagent that claims better yield yet forces small differences in your protocol. Computational biology is no different in that protocols and programs change slightly over time (usually in the form of version updates). In the "best" case, version improvements add new functionality that do not change old analysis, in the worst of cases in an effort to fix small bugs (thereby increase accuracy by eliminating false positives in the eyes of the developers at least) in a way that makes you unaware that anything has changed other than your final output if you have to repeat your analysis (say because you added new samples to your cohort). Sometimes, programs will change drastically enough that even your old commands stop working. This is both a blessing and a curse. A blessing in that you are astutely aware that something has changed, and you are forced to either fix/update your analysis to the new version (typically gaining an understanding of what was changed), and a curse in that you have to figure out how to fix things even if this means continuing to use an older version.

As an optional extension of this tutorial you will have the opportunity to experience this first hand as you  have access to 2 different versions of samtools 1 of which works for this tutorial, and the other which does not.

First let's check if SAMtools is loaded. The easiest way to do this is to simply type samtools. (Remember that most programs/commands are in all lowercase (while scripts often have capital letters) despite their webpages having capital letters associated with them to make them stand out). Looking through the output you should see a line that reads:

Version: 1.6 (using htslib 1.6)

This is very important information for the most detailed reporting of your computational analysis, and reproducibility of said analysis. Sadly this level of reporting is often ignored or not appreciated by many journals leading to difficulty in reproducing results.

Some modules on TACC offer multiple different versions, and sadly (for many biological modules at least), the default version is not always the newest version. Can you use the module system to determine if there are other versions of samtools available?

module list samtools
module avail samtools
module spider samtools

You should notice that the only version of samtools that is available through the module system on tacc is version 1.6 and that the module is currently loaded because of what we put in the .bashrc folder in your $HOME directory yesterday. Try to unload the samtools module and see if you have any other versions of samtools available in other locations.

module unload samtools

Somewhat unfortunately, there is no output given when a module is unloaded, even if you try to unload something that doesn't exist, or wasn't loaded currently:

tacc:~$ module unload not-a_real_module
tacc:~$ module unload samtools
tacc:~$

Now if you reuse the module list samtools command you will get a response saying that there are no modules matching samtools currently loaded. Yet what happens when you again try the samtools command without any other information? You clearly see a different version 0.1.18. Can you figure out where version 0.1.18 is being loaded from?

tacc:~$ which samtools 
/corral-repl/utexas/BioITeam/breseq/bin/samtools

So why is it when the module is loaded it finds the 1.6 version rather than the 0.1.18 version? The answer is thats what the $PATH variable is set to find. Consider the following information about the module system and the $PATH variable:

1. When you type a command, only locations that are in your PATH variable are searched for an executable command matching that name.
2. When the command is found in your PATH, the computer immediately substitutes the location it was found for the short command name you entered, and stops searching.
   1. This means that things that are early in your path are always searched first. In some extreme circumstances if you add a bunch of locations with lots of files to the front of your PATH, you can actually slow down your entire computer, so try to limit the path variable to only look in directories containing executable files.
3. The module system always assumes that when you load a module, you intend to use it, and thus puts the executables for that module at the front of your PATH. This is one of the reasons we try to limit the number of modules we load by default (it puts other commands further back in the list). 
4. In your .bashrc file, modules are loaded first (including samtools). 
5. After modules are loaded, we further manipulate your PATH variable several times. The last section involving breseq has 2 alternative manipulations:

   1. The first which you can see we have commented out:

      # export PATH=$BI/breseq/bin:$PATH

      1. This command says make the variable PATH equal to the variable BI plus /breseq/bin and then add on the existing value of $PATH

   2. The second we actually use.

      export PATH=$PATH:$BI/breseq/bin

      1. This command says make the variable PATH equal to the existing value of $PATH variable and then add on BI plus /breseq/bin 

6. One of the most important lessons you can ever learn

   Anytime you manipulate your PATH variable you always want to make sure that you include $PATH on the right side of the equation somewhere separated by : either before it, after it, or on both sides of it if you want it in the middle of 2 different locations. As we are explaining right now, there are reasons and times to put it in different relative places, but if you fail to include it (or include a typo in it by calling it say $PTAH) you can actually remove access to all existing commands including the most basic things like "ls" "mkdir" "cd".

module load samtools
samtools  # check output for version information
which samtools
 
#required output:
/opt/apps/intel18/samtools/1.6/bin/samtools

tacc:~$ which samtools
/opt/apps/intel18/samtools/1.6/bin/samtools

which -a samtools

Calling variants in reads mapped by bowtie2

Prepare your directories

Since the $SCRATCH directory on lonestar is effectively infinite for our purposes, we're going to copy the relevant files from our mapping tutorial into a new directory for this tutorial. This should help you identify what files came from what tutorial if you look back at it in the future. Let's copy over just the read alignment file in the SAM format and the reference genome in FASTA format to a new directory called GVA_samtools_tutorial.

cds
mkdir GVA_samtools_tutorial
cd GVA_samtools_tutorial
cp $SCRATCH/GVA_bowtie2_mapping/bowtie2/SRR030257.sam .
cp $SCRATCH/GVA_bowtie2_mapping/NC_012967.1.fasta .

cp: cannot stat '/scratch/01821/ded/GVA_bowtie2_mapping/bowtie2/SRR030257.sam': No such file or directory
cp: cannot stat '/scratch/01821/ded/GVA_bowtie2_mapping/NC_012967.1.fasta': No such file or directory

Index the FASTA reference file

First, you need to index the reference file. (This isn't the same as indexing it for read mapping. It's indexing it so that SAMtools can quickly jump to a certain base in the reference.)

samtools faidx NC_012967.1.fasta

Take a look at the new *.fai file that was created by this command see if you have any idea what some of the numbers mean. 

less NC_012967.1.fasta.fai  # can exit with "q"

As you can see, the less command also works perfectly well with files that are not in danger of crashing anything without cluttering your terminal  with lines of a file.

Convert mapped reads from SAM to BAM, sort, and index

SAM is a text file, so it is slow to access information about how any given read was mapped. SAMtools and many of the commands that we will run later work on BAM files (essentially GZIP compressed binary forms of the text SAM files). These can be loaded much more quickly. Typically, they also need to be sorted, so that when the program wants to look at all reads overlapping position 4,129,888, it can easily find them all at once without having to search through the entire BAM file.

The following 3 commands are used to:

1. convert from SAM to BAM format
2. sort the BAM file
3. index the sorted BAM file

As you might guess this is computationally intense and as such must be iDEV node or submitted as a job (more on this on Friday). If you want to submit them to the job queue, you will want to separate them with a ";" to ensure that they run sequentially rather than simultaneously as each uses the output of the previous command. Under no circumstances should you run this on the head node.

samtools view -b -S -o SRR030257.bam SRR030257.sam
samtools sort SRR030257.bam -o SRR030257.sorted.bam
samtools index SRR030257.sorted.bam

Examine the output of the previous commands to get an idea of whats going on. Here are some prompts of how to do that:

ls -1  # This is the number 1 not the letter L. Several people seem to get confused about this each year, it is not necessary for any reason other than to give a single column of output regardless of window size.

NC_012967.1.fasta
NC_012967.1.fasta.fai
SRR030257.bam
SRR030257.sam
SRR030257.sorted.bam
SRR030257.sorted.bam.bai

Call genome variants

Now we use the mpileup command from samtools to compile information about the bases mapped to each reference position. The output is a BCF file. This is a binary form of the text Variant Call Format (VCF).

samtools mpileup -u -f NC_012967.1.fasta SRR030257.sorted.bam > SRR030257.bcf

The samtools mpileup command will take a few minutes to run. As practice for a fairly common occurrence when working with the iDEV environment, once the command is running, you could try putting it in the background by pressing control-z and then typing the command bg so that you can do some other things in this terminal window at the same time. Remember, there are still many other processors available on this node for you to do other things! Just remember that if you have something running in the background you need to check in with it to see if it is still running with the ps command or watch the command line every time you execute a new command as you may see information about your background task having finished.

Convert genome variants to human readable format

Once the mpileup command is complete, convert the BCF file to a "human-readable" VCF file using the bcftools command (the which command will tell you where this command is located and examination of that path should tell you how you have access to it).

which bcftools
bcftools call -v -c SRR030257.bcf > SRR030257.vcf

What are these options doing?

SRR030257.bcf

> SRR030257.vcf

Take a look at the SRR030257.vcf file using less. It has a nice header explaining what the columns mean, including answers to some of your questions from yesterday's presentations. Below this are the rows of data describing potential genetic variants.

Analyzing variants detected

VCF format has alternative Allele Frequency tags denoted by AF= Try the following command to see what frequency our variants exist at.

grep AF1 SRR030257.vcf

If you look at the AF1= values you will all the lines are either ~ 0.5, or 1.

 awk -F";" '{for(i=1;i<=NF;i++){if ($i ~ /AF1/){print $i}}}' SRR030257.vcf

^splits each line into columns based on where the ";"s, then searches through each column, if the "AF1" is found in the column, that column is printed. From the output it is even clearer that frequencies are coming up.

 awk -F";" '{for(i=1;i<=NF;i++){if ($i ~ /AF1/){print $i}}}' SRR030257.vcf | sort

cat SRR030257.vcf | grep AF1=1 > SRR030257.filtered.vcf


grep AF1=1 SRR030257.vcf > SRR030257.filtered.vcf

This is does give us exactly what we asked for: all the lines that show a variant allele frequency of 1. Unfortunately, we lost all the useful header information at the top of the original  SRR030257.vcf file. 

cat SRR030257.vcf | grep -v AF1=0 > SRR030257.filtered.vcf

grep -v AF1=0 SRR030257.vcf > SRR030257.filtered.vcf

Will preserve all lines that don't have 'AF1=0' value on the line and is one way of doing this. If you look closely at the non-filtered file you will see that the frequencies are given as AF1=0.### so by filtering out lines that have 'AF1=0' in them we get rid of all frequencies that are not 1, including say 'AF1=0.99'. 

cat SRR030257.vcf | grep -v AF1=0.[0-8] > SRR030257.filtered.vcf

grep -v AF1=0.[0-8] SRR030257.vcf > SRR030257.filtered.vcf

Return to GVA2020 course page.

Optional Exercises at the end of class or for Wednesday/Thursday choose your own tutorial time.

Calling variants in trimmed reads.

1. Trim both Read1 and Read2 using info from read preprocessing tutorial.
2. Map reads with bowtie2 using info from read mapping tutorial.
3. Call variants using this tutorial.

Remember in the intro tutorial we talked about file/directory naming. Be sure you don't write over your old files. Maybe create a new directories like GVA_samtools_bowtie_improved for the outputs.

Further Optional Exercises

• Which mapper finds more variants?
• Can you figure out how to filter the VCF files on various criteria, like coverage, quality, ... ?
• How many high quality mutations are there in these E. coli samples relative to the reference genome?
• Look at how the reads supporting these variants were aligned to the reference genome in the Integrative Genomics Viewer (IGV). This will be a separate tutorial for tomorrow.

Other version of samtools

As suggested in the initial introduction, the point of this optional tutorial is to work through getting a different version of samtools to work (the command line expectations, flags, and subcommands (ie bcftools call) were not what they are now in version 0.1.18). To make sure you are starting in the right place:

tacc:~$ module unload samtools
tacc:~$ which samtools
/corral-repl/utexas/BioITeam/breseq/bin/samtools

 
mkdir BDIB_samtools_old_version_tutorial
cd BDIB_samtools_old_version_tutorial
cp $SCRATCH/BDIB_bowtie2_mapping/bowtie2/SRR030257.sam .
cp $SCRATCH/BDIB_bowtie2_mapping/NC_012967.1.fasta .

Good luck, and remember if you undertake this and get frustrated with it, it is a great learning experience and is probably the most difficult exercise/tutorial in this class. As part of the learning experience, feel free to contact me with any questions or problems you are specifically having with it, but cookbooked suggestions would defeat the intended purpose of beating your head against the problem to figure it out. You DO have the necessary skills to figure out how to do this now. 

Return to GVA2020 course page.