Overview

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• Why are some reads different colors? Hint: Try changing the display options to show read pairs and editing some of the distance constraints.

• Interested in determining the probability that a read is not where it should be? What is a typical mapping quality (MQ) for a read?

  Expand
  title Click here for the formula.
  The estimated probability that a read is mapped incorrectly is 10^(-MQ/10). Where MQ is the mapping quality.

• Can you find a variant where the sequenced sample differs from the reference? This would be like looking for a needle in a haystack if not for the use of variant callers and the control-f and control-b options to zoom right to areas where there are discrepancies between reads and the reference genome that might indicate there were mutations in the sequenced E. coli.

  What is going on in the pykF gene region? You might see red read pairs. What does that mean? Can you guess what type of mutation occurred here?

  See if you can find more interesting locations. There are ~40 mutations total in this sample MOST of which are false positives.

  Expand
  title Some interesting example coordinates
  Expand title Coordinate 161,041. What gene is this in and what is the effect on the protein sequence? Gene is pcnB, mutation is a snp Expand title Coordinate 1613,248,041957. What gene is this in and what is the effect on the protein sequence? Gene is pcnBinfB, mutation is a snp Expand title Coordinate 3,248,957. What gene is this in and what is the effect on the protein sequence? Gene is infB, mutation is a snp Expand title Coordinate 3,894,997. What type of mutation is this? Deletion of the rbsD gene Expand title Check out the rbsA gene region? What's going on here? There was a large deletion. Can you figure out the exact coordinates of the endpoints? Navigate to coordinate 3,289,962. Compare the results for different alignment programs and settings. Can you explain what's going on here?
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  Answer	Answer
  There is a 16 base deletion in the gltB gene reading frame.
  Expand
  Answer	Answer
  The read pairs are discordantly mapped. There was an insertion of a new copy of a mobile genetic element (an IS150 element) that exists at other locations in the reference sequence.

Workflow 2: Viewing Human Genome Data in IGV

Now that you've familiarized yourself with IGV using a "simple" bacteria, let's look at something a "little" more complex: the human genome.

Advanced exercise: human data scavenger hunt 

Data from the 1000 Genomes Project can be found directly from the Broad's server for IGV. There are now MANY genomes available this way.

Find one or more dbSNP accession numbers for SNPs apparent in one of the two 1000 genomes project trios in the GABBR1 gene.

Steps:

1. Download and install the Integrative Genome Viewer from the Broad Institute. 
2. Select "Human hg19" as the reference genome from the top left drop down (you may need to select "more" to have hg19 as an option)
3. Get some data: File > Load from Server… > 1000 genomes > Alignments > ACB > exome > HG01880
4. Navigate to the rightmost exons of the GABBR1 gene.
5. Zoom in until you find some SNPs. (Hint look just to the left of the 2nd exon).
6. What type of library is this? (Hint: zoom out)
7. If you knew this was a cancer patient, consider how strongly you would think this may be a potentially causative mutation.
8. Imagine it was actually in the exon rather than just into the intron... would that make you consider it more?
9. Load and look at the SNP track: File > Load from server > Annotations > Variants and Repeats > dbSNP 1.4.7
10. The track may load with the Refseq genes, making it useful to resize that window to view both the gene and the dbSNP information simultaneously.
11. Consider if this makes you think it more likely or less likely that this is a causative mutation.

Optional Tutorial Exercises ...

samtools faidx NC_012967.1.fasta
samtools view -b -S -o bowtie/SRR030257.bam bowtie/SRR030257.sam
samtools sort bowtie/SRR030257.bam -o bowtie/SRR030257.sorted
samtools index bowtie/SRR030257.sorted.bam

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Another useful trick with either IGV or UCSC: displaying your own BLAST results: BioPerl allows for super-easy conversion from blast output to a gff file; IGV and the UCSC browser both understand GFF files. The short script bl2gff.pl does the conversion. Let's use the blast result we had from a hypothetical test for the JAG1 gene to show you how. You'll need to provide the output file from your blast job as the input to the script (in this case "blast_jag1.058638".

grep '^gi' blast_jag1.o586038 > jag1_blast.out
module load perl
module load bioperl
bl2gff.pl jag1_blast.out > jag1_blast.out.gff

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• Expand title Coordinate 3,894,997. What type of mutation is this? Deletion of the rbsD gene Expand title Check out the rbsA gene region? What's going on here? There was a large deletion. Can you figure out the exact coordinates of the endpoints? Navigate to coordinate 3,289,962. Compare the results for different alignment programs and settings. Can you explain what's going on here? Expand Answer Answer There is a 16 base deletion in the gltB gene reading frame. What is going on in the pykF gene region? You might see red read pairs. What does that mean? Can you guess what type of mutation occurred here? Expand Answer Answer The read pairs are discordantly mapped. There was an insertion of a new copy of a mobile genetic element (an IS150 element) that exists at other locations in the reference sequence. See if you can find more interesting locations. There are ~40 mutations total in this sample MOST of which are false positives.

Workflow 2: Viewing Human Genome Data in IGV

Now that you've familiarized yourself with IGV using a "simple" bacteria, let's look at something a "little" more complex: the human genome.

Advanced exercise: human data scavenger hunt 

Throughout this class we have used the wget command several times to download files to TACC which is running bash on a linux environment. As IGV only works on your local computer rather than TACC, downloading files directly to your laptop is more practical. Unfortunately wget is a linux only command and unix does not have it so instead we shall use the curl command to download some human data to IGV and look at it. The following commands should be run in a terminal window that is not logged into tacc.

cd ~/Desktop
mkdir human_IGV
cd human_IGV
curl -O https://xfer.genome.wustl.edu/gxfer1/project/gms/testdata/bams/hcc1143/HCC1143.normal.21.19M-20M.bam
curl -O https://xfer.genome.wustl.edu/gxfer1/project/gms/testdata/bams/hcc1143/HCC1143.normal.21.19M-20M.bam.bai

These if you look at the file names, you may notice that this bam file and its index correspond to human chromosome 21 from 19 million to 20 million bases. This limited data set is to hopefully avoid IGV crashing. 

Steps:

1. Close IGV (if you have it open from the first tutorial with your mapping, SNV, and SV data) and reopen it. 
2. Select "Human hg19" as the reference genome from the top left drop down (you may need to select "more" to have hg19 as an option)
3. Load the bam files you downloaded: File > Load from File…  and select HCC1143.normal.21.19M-20M.bam
4. Turn on dbSNP annotations File > Load from Server… > Tutorials > Variants > dbSNP 1.3.1
5. Right click on the track name on the left and select sort alignments by start location
6. There are 2 mutations visible in the chr21:19,479,237-19,479,814 region answer the following questions:
   1. Are both SNPS supported by reads mapping to both the forward and reverse DNA strand (hint: make sure reads are colored by strand)?
      

   2. Which is more likely to be related to disease? why?

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      title Answers
      a. Yes, both forward and reverse reads (red and blue if colored by strand) contain the SNPs compared to the reference b. The one on the left does not correspond to a dbSNP entry and is therefore more likely to be related to disease state

      
      

7. There are 2 SNPs visible in the chr21:19,666,833-19,667,007 region. Answer the following questions:

   1. Two mutations very close together is often a case of poor alignment scores. Is that the case here (remember this is human data)?

   2. Is either likely to be related to disease? 

      Expand
      title Answers
      a. No, each read only has 1 mutation on it, these are 2 different alleles each with its own SNP relative to 'wt'. Both are reported in dbSNP b. Neither is likely to be related to disease or at least to rare disease as both mutations have previously been identified as naturally occurring by dbSNP

      
      

8. What is going on in the chr21:19,324,469-19,331,468 region?

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   title Answers
   Homozygous deletion. In the track on the left, right click and select 'view as pairs' to see linkage between R1 and R2 to see individual reads mapping to both sides of the deletion

   
   

9. What is going on in the chr21:19,102,154-19,103,108 region?

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   title Answers
   This is an example of poor alignment to a repetitive AluY element. Notice how of the read pairs that map with numerous SNPs have 1 read that maps with lots of SNPs and the other read maps with none? This is caused by mapping reads to a limited area of the whole genome, if these reads had been allowed to map to the entire genome it is very likely that both read pairs would map without SNPs somewhere else in the genome.

   
   

10. What other interesting things can you find?

Optional Tutorial Exercises ...

samtools faidx NC_012967.1.fasta
samtools view -b -S -o bowtie/SRR030257.bam bowtie/SRR030257.sam
samtools sort bowtie/SRR030257.bam -o bowtie/SRR030257.sorted
samtools index bowtie/SRR030257.sorted.bam

You can use IGV to visualize mapped reads and predicted variants from any later tutorial!

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