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.
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?
Remember we use the the base command "
As you have used the module system several times now, you probably should have been at least in the right ballpark with the hint if not sooner. |
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 $HOME directory yesterday. Try to unload the samtools module and see if you have any other versions of samtools available in other locations.
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Somewhat unfortunately, there is no output given when a module is unloaded, even if you try to unload something that doesn't exist, or wasn't loaded currently:
tacc:~$ 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?
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Hopefully, you recognize this as part of the BioITeam community resources. |
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 $PATH variable:
The first which you can see we have commented out:
# export PATH=$BI/breseq/bin:$PATH |
The second we actually use.
export PATH=$PATH:$BI/breseq/bin |
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". |
Simply reload samtools using the module system, check the version, and which version is now being used.
If this doesn't seem familiar or make sense, get my attention on zoom. |
execute the following command and make sure you get the 2nd line as output:
If you see something different get my attention or the tutorial will not work. |
A lot of text was just devoted to the $PATH variable and how its manipulated and how to investigate it in a few different ways. This is because PATH variables are fairly common, especially when if start experimenting with multiple different programs that may have similar underlying requirements.
When you have multiple results, the top line is the line that will be used unless you specify the entire path to the command. This can be useful in diagnosing what is going wrong particularly when you have an error message that says a command didn't work, and |
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 . |
If you see messages saying something similar to the following:
It suggests something you either did not yet complete the mapping tutorial, or more likely, you stored these files in a different directory. If you think you completed the mapping tutorial, get my attention and be ready to share your screen and I'll try to help you find your missing files. When copy commands execute successfully, the expected output is silent (no output at all) |
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.
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:
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.
Use showq -u to verify you are still on the idev node. If not, and you need help getting a new idev node, see this tutorial. |
samtools view -b -S -o SRR030257.bam SRR030257.sam samtools sort SRR030257.bam -o SRR030257.sorted.bam samtools index SRR030257.sorted.bam |
| This is a really common sequence of commands, so you might want to add it to your personal cheat sheet. |
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 |
Sure enough, it's the index file for the BAM file. |
You might be tempted to On the other hand, compressing SAM files will save a fair bit of space, but the conversion between bam back to sam is pretty simple. Making storage of bam files likely a better decision. |
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 |
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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.
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 |
which bcftools returns the following line: /opt/apps/intel18/samtools/1.6/bin/bcftools You may recognize from above that it is the same directory samtools is found in when you load samtools with the module system. |
What are these options doing?
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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.
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 $i}}}' SRR030257.vcf
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^splits each line into columns based on where the ";"s, then searches through each column, if the "AF1" is found in the column, that column is printed. From the output it is even clearer that frequencies are coming up.
| This is a pretty useful awk 1 liner to keep track of for pulling a single column out when you know it will have an identifier but not what column it will occur in; just substitute what you expect to find for "AF1" and whatever you want to use to break the line up for ";" (with \t for tab and , being the 2 most common options for tsv and csv files respectively). |
awk -F";" '{for(i=1;i<=NF;i++){if ($i ~ /AF1/){print $i}}}' SRR030257.vcf | sort
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After you ran the bcftools call command you saw: "Note: none of --samples-file, --ploidy or --ploidy-file given, assuming all sites are diploid". Just like on a webpage you can use control/command + F to find specific text in the window. Lookf for 'diploid' and you should see the line referenced above. Obviously this suggests a way that you could go back and reanalyze this data introducing one of the recommended flags to the bcftools call command and see how this might effect your analysis. If you choose to do this, I suggest adding descriptive file name between 'SRR030257' and '.vcf' to make the results easier to compare. |
An initial attempt might be something like this:
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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.
From 'grep -h' you can see the that the '-v' inverts the match so it will print everything EXCEPT for lines that match.
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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'.
Remember from our Raw Sequencing Data tutorial yesterday that we can group certain characters together by placing them between square brackets [].
Here we added a decimal point after the 0, and then allowed for a match to any digit between 0 and 8. Thus lines that have AF1=1 would not match, nor would a line with AF1=0.9 . |
Return to GVA2020 course page.
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.
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.
The 2016 class did this tutorial in the opposite manner where the 0.1.18 version was given as the walkthrough rather than the 1.6 version. I strongly suggest you use that tutorial only as a way to check your answers, but that tutorial can be found here. |
Return to GVA2020 course page.