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:
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.
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 |
|---|---|---|
| Paired-end Illumina, First of mate-pair, FASTQ format | Re-sequenced E. coli genome |
| Paired-end Illumina, Second of mate-pair, FASTQ format | Re-sequenced E. coli genome |
| Reference Genome in FASTA format | E. coli B strain REL606 |
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
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:
--rftells bowtie2 that your read pairs are in the "reverse-forward" orientation of a mate-pair library-X 5000tells 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
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?
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:
<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 create a tab-delimited file of chromosome lengths named NC_012967.1.lengths. YOU CAN NOT COPY PASTE THIS COMMAND!
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.
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 - -
