Overview

Most approaches for predicting structural variants require you to have paired-end or mate-pair reads. They use the distribution of distances separating these reads to find outliers and also look at pairs with incorrect orientations. As mentioned during several of the presentations, many researchers choose to ignore these types of mutations and combined with the increased difficulty of accurately identifying them, the community is less settled on the "best" way to analyze them. Here we present a tutorial on SVDetect based on the quality of its instructions, and easy of installation despite its use of relatively hefty configuration files.

Other possible tools:

BreakDancer - hard to install prerequisites on TACC. Requires installing libgd and the notoriously difficult GD Perl module.
PEMer - hard to install prerequisites on TACC. Requires "ROOT" package.

Good discussion of some of the issues of predicting structural variation:

http://www.genome.gov/Pages/Research/DER/1000GenomesProjectTutorials/StructuralVariants-JanKorbel.pdf

Example: E. coli genome with structural variation

Here's an E. coli genome re-sequencing sample where a key mutation producing a new structural variant was responsible for a new phenotype involving citrate, one of Dacia's favorite topics.

suggested directory set up

cds
cp -r $BI/gva_course/structural_variation/data BDIB_sv_tutorial
cd BDIB_sv_tutorial

This is Illumina mate-paired data (having a larger insert size than paired-end data) from genome re-sequencing of an E. coli clone.

File Name	Description	Sample
`61FTVAAXX_2_1.fastq`	Paired-end Illumina, First of mate-pair, FASTQ format	Re-sequenced E. coli genome
`61FTVAAXX_2_2.fastq`	Paired-end Illumina, Second of mate-pair, FASTQ format	Re-sequenced E. coli genome
`NC_012967.1.fasta`	Reference Genome in FASTA format	E. coli B strain REL606
NC_012967.1.lengths	Simple tab delimtered file based on the size of the reference needed for SVDetect so you don't have to create it yourself

Map data using bowtie2

First we need to (surprise!) map the data. This will hopefully reinforce the bowtie2 tutorial you just completed, but if you are feeling adventurous you could use BWA as optional reinforcement.

Do not run on head node

Make sure you are on an idev node using the command: showq -u

If you need a new idev node

idev  -m 120 -r CCBB_5.23.17PM -A UT-2015-05-18

bowtie2-build NC_012967.1.fasta NC_012967.1
bowtie2 -p 48 -X 5000 --rf -x NC_012967.1 -1 61FTVAAXX_2_1.fastq -2 61FTVAAXX_2_2.fastq -S 61FTVAAXX.sam

Possibly unfamiliar options:

--rf tells bowtie2 that your read pairs are in the "reverse-forward" orientation of a mate-pair library
-X 5000 tells bowtie2 to not mark read pairs as discordant unless their insert size is greater than 5000 bases.

You may notice that these commands complete pretty quickly. Always remember speed is not necessarily representative of how taxing something is for TACC's head node, and always try to be a good TACC citizen and do as much as you can on idev nodes or as job submissions

If you use version 1 of bowtie to do your mapping (or several other mapping programs), you won't predict any read SVs. Why?

bowtie doesn't output discordantly mapped pairs!

Run SVDetect

The first step is to look at all mapped read pairs and whittle down the list only to those that have an unusual insert sizes (distances between the two reads in a pair).

BAM_preprocessingPairs.pl -p 0 61FTVAAXX.sam

As we discussed in our earlier presentation, SV are often detected by looking for variations in library insert sizes. The stdout of the pearl script will answer the questions:

What is the normal insert size for this library?
What percent of reads appear to be associated with potential structural variants?
What percent of reads suggest potential novel sequence insertions or contamination with other sources of DNA?
How can you use the above answers to make characterizations about new sequencing data, or use this type of analysis to make implications about your overall sequencing?

Answers from the std output

-- using -1142.566-5588.410 as normal range of insert size
Approximately 20% based on:
-- 994952 mapped pairs
---- 195705 abnormal mapped pairs
Approximately 0.5% based on:
-- Total : 1000000 pairs analysed
-- 5048 pairs whose one or both reads are unmapped
Consider the following:
1. The first answer can tell you what type of library it is if you did not know ahead of time (remember paired end reads have ~500-700bp inserts on average not 1000s of bp)
2. This should help underscore that a significant portion of your total reads (and thus variation) may be in structural variants. Unfortunately, this does require generating a mate-pair library to learn.
3. Low levels of unmapped read pairs suggests that both the reference is accuate, of a high quality, and free of contamination.
  1. Note that contamination in this case refers only to other organisms, not other samples.

SVDetect demonstrates a common strategy in some programs with complex input where instead of including a lot of options on the command line, it reads in a simple text file that sets all of the required options. Lets look at how to create a configuration file:

You'll need to substitute the output of the pwd command on lines 7 and 8 below in front of "/full/path/to/" , but you will need to leave "61FTVAAXX.ab.sam" and "NC_012967.1.lengths".

Create the file svdetect.conf with this text

<general>
input_format=sam
sv_type=all
mates_orientation=RF
read1_length=35
read2_length=35
mates_file=/full/path/to/61FTVAAXX.ab.sam
cmap_file=/full/path/to/NC_012967.1.lengths
num_threads=48
</general>

<detection>
split_mate_file=0
window_size=2000
step_length=1000
</detection>

<filtering>
split_link_file=0
nb_pairs_threshold=3
strand_filtering=1
</filtering>

<bed>
  <colorcode>
    255,0,0=1,4
    0,255,0=5,10
    0,0,255=11,100000
  </colorcode>
</bed>

You also need to make sure you have a copy of the tab-delimited file of chromosome lengths named NC_012967.1.lengths. YOU CAN NOT COPY PASTE THIS COMMAND into a new file for 2 reasons! The first reason you can't copy the command is the tab characters don't translate correctly. The second is the nano text editor is not available on the compute nodes, and learning to use the vim editor for a single line is way more work than it is worth. Make sure the the NC_012967.1.lengths file has the following structure up to the comment, and that the <tab> is replaced with an actual tab character.

File NC_012967.1.lengths

1<tab>NC_012967<tab>4629812  # Use the tab key rather than writing out <tab>!!

The following commands will take a while and must be completed in order, so no advantages/ability to have them run in the background. Consult the manual for a full description of what these commands and options are doing while the commands are running.

Commands to run SNVDetect

SVDetect linking -conf svdetect.conf
SVDetect filtering -conf svdetect.conf
SVDetect links2SV -conf svdetect.conf

Take a look at the resulting file: 61FTVAAXX.ab.sam.links.filtered.sv.txt. Another downside of command line applications is that while you can print files to the screen, the formatting is not always the nicest. On the plus side in 95% of cases, you can directly copy the output from the terminal window to excel and make better sense of what the columns actually are

We've highlighted a few lines below:

chr_type        SV_type BAL_type        chromosome1     start1-end1     average_dist    chromosome2     start2-end2     nb_pairs        score_strand_filtering  score_order_filtering   score_insert_size_filtering     final_score     breakpoint1_start1-end1 breakpoint2_start2-end2
...
INTRA   NORMAL_SENSE    -       chrNC_012967    599566-601025   -       chrNC_012967    663036-664898   430     100%    -       -       1       -       -
...
INTRA   NORMAL_SENSE    -       chrNC_012967    3-2025  -       chrNC_012967    4627019-4628998 288     100%    -       -       1       -       -
...
INTRA   REVERSE_SENSE   -       chrNC_012967    16999-19033     -       chrNC_012967    2775082-2777014 274     100%    -       -       1       -       -

Any idea what sorts of mutations produced these three structural variants?

1. This is a tandem head-to-tail duplication of the region from approximately 600000 to 663000.
2. This is just the origin of the circular chromosome, connecting its end to the beginning!
3. This is a big chromosomal inversion mediated by recombination between repeated IS elements in the genome. It would not have been detected if the insert size of the library wasn't > ~1,500 bp!

... Many of the others are due to new insertions of transposable elements.

click here for installation instructions

Optional: Install SVDetect

We have installed SVdetect for you already as installation is a bit difficult (though still much easier than the alternatives listed in the introduction). You can verify it's location using which SVDetect in your $PATH under $BI/bin. One of the advantages (or disadvantages) of using the communal resource is that someone else can update all the necessary programs and packages for you. Alternatively, you can make a personal copy of the program yourself using the following commands. NOTE that this is presented mostly to underscore how spoiled we are with modules and the BioITeam.

Install SVDetect scripts

Navigate to the SVDetect project page

More information:

SVDetect code repository
SVDetect Paper

Download the code onto TACC.

wget https://sourceforge.net/projects/svdetect/files/latest/download
tar -xvzf SVDetect_r*.tar.gz
cd SVDetect_r*

Move the Perl scripts and make them executable

cp bin/SVDetect $HOME/local/bin
chmod 775 scripts/BAM_preprocessingPairs.pl
cp scripts/BAM_preprocessingPairs.pl $HOME/local/bin

Install required Perl modules

SVdetect requires a few Perl modules to be installed. In the default TACC environment, you can use the cpan shell to install most well-behaved Perl modules (with the exception of some complicated ones that require other libraries to be installed or things to compile). Here's how:

Install Perl modules required for SVDetect

login1$ module load perl
login1$ cpan
...
cpan[4]> install Config::General
...
cpan[4]> install Tie::IxHash
...
cpan[4]> install Parallel::ForkManager
...
cpan[4]> quit
login1$

Return to GVA2017 course page.

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