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qsv

Ollie Holmes christina Xu

Introduction

qSV is a sensitive multi-method structural variant detection tool that has been developed for whole genome paired end or mate pair sequencing. This implementation of qSV integrates independent findings from soft clipping and discordant mapped pair analyses and increases accuracy of breakpoint, micro homology and non template sequence detection by the incorporation of a localized de novo assembly of abnormal reads and split contig alignment.

Installation

qSV requires java7 and a machine with 8 cores (hyperthreaded) and at least 40GB of RAM.

Download the qsv tar file
Untar the tar file into a directory of your choice
You should see jar files for qsv and its dependencies:

[oholmes@minion0 qsv]$ tar xjvf qsv-0.3.tar.bz2
x antlr-3.2.jar
x htsjdk-1.140.jar
x ini4j-0.5.2-SNAPSHOT.jar
x jopt-simple-4.6.jar
x picard-lib.jar
x qbamannotate-0.3pre.jar
x qbamfilter-1.2.jar
x qcommon-0.3.jar
x qio-0.1pre.jar
x qpicard-1.1.jar
x qsv-0.3.jar
x trove-3.1a1.jar
[oholmes@minion0 qsv]$

Dependencies

Before running qSV, you must install the BLAT software suite.

Usage

qsv requires 2 arguments in order to run:

  • an ini file containing details of the paramters to be used
  • a path to a directory where temporary file will be written to.

Run the following command to start execution.

java -Xmx40g -jar /full/path/qsv-0.3.jar -ini /full/path/qsv.demo.ini  -tmp /tmp/directory

Ini file

qSV has two modes which can be run separately or together:

  • Discordant pair mode (pair)
  • Soft clipping mode (clip)

An example ini file follows:

[general]
log = name of log file
loglevel = INFO or DEBUG
sample = donor or patient id 
sv_analysis = Type of sv analysis: pair, clip, both
output = output directory
reference = path to fasta reference file
platform=solid or illumina
min_insert_size = minimum size of SV insert. Default 50. 
isize_records=number of records per read group used to calculate isize
range=specify one or more chromosomes or inter for translocations
repeat_cutoff=specified number of clipped reads to define a potential repeat region

[pair]
pairing_type = type of reads: lmp (solid Long Mate Pair), pe (Paired End) or imp (illumina mate-pair)
mapper = mapping eg bioscope, lifescope, bwa,bwa-mem, novoalign
pair_query = Filtering query for discordant pairs eg. and(Cigar_M> 34, option_SM>10, MD_mismatch < 3, Flag_DuplicateRead == false) 
cluster_size = number of discordant reads required to define a cluster
filter_size = number of control reads in a cluster to classify it germline


[clip]
clip_query = Filtering query for clips: eg and(Cigar_M> 34, MD_mismatch < 3, MAPQ >0,Flag_DuplicateRead == false) 
clip_size = number of reads required to proceed with soft clip SV signature detection
consensus_length = minimum length of soft clip consensus sequence
blatpath = path to blat executable /home/Software/BLAT
blatserver = name of blat server eg:localhost
blatport = port for blat server
single_side_clip = If SV signatures with soft clip evidence at one breakpoint should be included 

[test]
name = id for the sample 
input_file = location of the test/disease bam. Must be co-ordinate sorted

[test/size_1]
rgid = Read Group ID
lower = lower insert size
upper = upper insert size

[control]
name = id for the control sample 
input_file = location of the control sample

[control/size_1]
rgid = Read Group ID
lower = lower insert size
upper =  upper insert size

A more detailed description of the ini file options is listed in the table below:

Section Option Required/Optional Description [Default value]
general log optional Name of log file [sample_name.log]
loglevel optional Logging level required, e.g. INFO,DEBUG. [INFO]
sample required Donor/sample id eg PatientA
sv_analysis optional Use this option to specify what type of sv_analysis will be carried out in qsv. - pair: discordant pair SV detection - clip: soft clipping SV detection - both: SV detection using both discordant pairs and soft clips [both]
output required Output directory. A results folder for the analysis will be automatically created based on sample and date. Eg. output directory is /home/test/qsv. Results will be written to: /home/test/qsv/qSV_patientA_20121025_1111
reference required Path to the reference genome file. Must also have a .fai index file. This can be generated using samtools ‘faidx’ program [1]
platform required Platform used for sequencing: solid or illumina [illumina]
min_insert_size optional Minimum size of insert for potential SVs. [50]
range optional Specify one or more chromosomes. Specify inter for translocations.
repeat_cutoff optional The number of clipped reads that will define define a potential repeat region (see SV category 5) [1000]
pair pairing_type Required for discordant pair Specify the type of read pairing used: - lmp =solid long mate pair - imp (illumina mate pair) - pe = paired end [pe]
mapper Required for discordant pair Mapping tool used to map reads: - for lmp: bioscope or lifescope - for pe: bwa [bwa]
pair_query optional The filtering query to filter the discordant pair reads. (See FILTER OPTIONS) Default is: - If minimal/no filtering is required, use: Flag_DuplicateRead == false [- for lmp: and(Cigar_M> 35, option_SM> 14, MD_mismatch< 3, Flag_DuplicateRead == false) - for pe or imp: and(Cigar_M> 35, option_SM> 10, MD_mismatch< 3, Flag_DuplicateRead == false)]
cluster_size optional Number of reads required to define a cluster. [3]
filter_size optional Number of control reads in a cluster required to call the cluster germline. [1]
clip clip_query optional The filtering query to filter the soft clipped reads. (See FILTER OPTIONS) [and(Cigar_M> 34,MD_mismatch < 3,MAPQ >0,Flag_DuplicateRead == false)]
clip_size optional Number of clipped reads required to proceed with soft clip SV signature detection. [3]
consensus_length optional Minimum length of soft clip consensus sequence. [20]
blatpath Required for soft clipping Path to blat executable /home/Software/BLAT
blatserver Required for soft clipping Name of blat server eg: localhost
blatport Required for soft clipping or local split read contig Port for blat server: eg 8000
single_side_clip optional Set to true if SV signatures with soft clip evidence at one breakpoint should be identified
test name required Name of the test sample eg tumour
input_file required Path to the test bam. Must be co-ordinate sorted
test/size : Use nomenclature test/size_numbe eg test/size_1, test/size_2 etc) rgid required Read Group ID. Found in the header of the bam
lower required Lower insert size
upper required Upper insert size
control name required Name of the control sample eg. normal
input_file required Path to the control bam. Must be co-ordinate sorted
control/size : Use nomenclature control/size_number e.g. control/size_1, control/size_2 etc) rgid required Read Group ID. Found in the header of the bam
lower required Lower insert size
upper required Upper insert size

Filter Options

  • Input bam file reads undergo filtering to ensure high quality reads (see ini file options: pair_query and clip_query).
  • Filtering queries list one or more conditions joined by operators. There are currently only two operators available and and or. Filter queries are in the format:
“operator (condition, condition, query)”
  • You can also insert query language as a condition into the final query string. For example this query string, joined by operator and contains three conditions. Here we treat the sub query or (MAPQ > 50, option_ZM == 1) as one condition:
“and (Cigar_M>35, or (MAPQ> 50, option_SM ==1), Flag_DuplicateRead == false)”
  • A condition statement is of the form:
“key comparator value”

The below table lists current options available for important BAM fields:

BAM Field Key Comparator Value Examples
Flag flag_ReadPaired "==" string to report all duplicated reads: flag_duplicated == true flag_duplicated != 0
flag_ProperPair "!="
flag_ReadUnmapped
flag_Mateunmapped
flag_ReadNegativeStrand
flag_MateNegativeStrand
flag_FirstOfpair
flag_SecondOfpair
flag_NotprimaryAlignment
flag_ReadFailsVendorQuality
flag_DuplicateRead
Cigar Cigar_I "==" int to report all reads with mapped base more than 15 Cigar_M>= 16 Cigar_M> 15
Cigar_D "!="
Cigar_N ">="
Cigar_S "<="
Cigar_H ">"
Cigar_P "<"
Cigar_M
MAPQ MAPQ "==" int to report all reads with higher mapping quality than 16 MAPQ > 16
"!="
">="
"<="
">"
"<"
Optional field option_<tag> "==" string To report the tag “RG” with value :: Tumor Option_RG == Tumor
"!="
Optional field option_<tag> "==" int to report the tag “SM” which has a value greater than 14 option_SM> 14
"!="
">="
"<="
">"
"<"

Insert Size Options

Discordant pair mode requires the provision of a normal range of expected insert sizes for paired sequencing reads (lower and upper isize). This can be attained as follows:
1. use Picard's CollectInsertSizeMetrics to give you an ISize distribution
2. use qProfiler

Once the user has calculated the expected insert size ranges, they should be added in the ini file (see ini file options test/size section and control/size section)
An upper and lower insert size must be provided for each read group in the input bam file/s.

Input Files

qSV takes mapped next-generation sequencing data as input. It has been tested with:

  • SOLiD long-mate paired and paired-end sequencing data mapped using bioscope or lifescope (discordant pair mode only).
  • Illumina paired-end sequencing data mapped using BWA (discordant pair and soft clipping modes).
  • Illumina long mate paired sequencing data mapped using BWA (discordant pair and soft clipping modes).

To determine somatic and germline events, qSV requires 2 input files in the BAM file format which are co-ordinate sorted:

  • the test data file (ie disease/tumour) file
  • comparison file (ie control/normal) file

To identify SVs with a single test sample (no comparison with control sample), qSV requires 1 input file in the BAM file format which is co-ordinate sorted.

  • the test data file (ie disease/tumour) file

For discordant pair mode each sequencing record must contain several fields that are described in the SAM format specification (1):

  • MD: string for mismatching positions
  • SM: template-independent mapping quality (if using default filtering query)
  • NH: number of reported alignments that contains the query in the current record. If the reads have been mapped using BWA, the NH flag is not necessary if the records contains the BWA specific fields: X0, XA

For soft-clipping mode, we recommend the reads are mapped by BWA. (Other mapping algorithms can be added).

Output Files

qSV will generate a number of output files.

Log file:

  • eg. PatientA_test_control.log
  • record of activities for the qSV analysis

Summary file:

  • eg. PatientA.qsv.summary.txt
  • summarizes parameters used in the qSV analysis

Tab delimited structural variants file:

  • eg. PatientA.somatic.sv.txt; PatientA.germline.sv.txt
  • Files generated for germline and somatic events
  • Summary of structural variants identified in a tab-delimited text file with the columns:
Header Description
analysis_id in format of qSV_sample_date_time
sv_id id of the structural variant
sm = somatic
gm = germline
sv_type DEL/ITX – deletion/other intrachromosomal
CTX – interchromosomal translocation
DUP/INS/ITX – duplication/insertion/other intrachromosomal
INV/ITX – inversion/other intrachromosomal
chr1 chromosome 1 of SV
pos1 position 1 of SV
strand1
chr2 chromosome 2 of SV
pos2 position 2 of SV
strand2
test_discordant_pairs_count number of discordant pair reads which pass the filter from test bam that support the current SV
control_discordant_pairs_count number of discordant pair reads which pass the filter from control bam that support the current SV
control_low_qual_reads_count number of low quality discordant pair reads from control bam for the current SV. These reads are lower quality reads from the controlbam that were excluded by the original filtering parameters. Presence of a large number of the reads may indicate the event is germline rather than somatic.
test_clips_count_pos1 number of high quality soft clipped reads at position1 from test/disease bam that support the current SV
test_clips_count_pos2 number of high quality soft clipped reads at position2 from test/disease bam that support the current SV
control_clips_count_pos1 number of high quality soft clipped reads at position1 from control bam that support the current SV
control_clips_count_pos2 number of high quality soft clipped reads at position2 from control bam that support the current SV
microhomology bases of microhomology found. If microhomology was tested, and no microhomology found, the result will be “not found”. If microhomology was not tested this column will list: “not tested”
non-template bases of non-template sequence found. If non-template was tested, and no non-template was identified, the result will be “not found”. If no non-template was not tested result will be: “not tested”
Category Evidence for the SV (1-6)
1. High level of evidence: eg discordant pair evidence, clipping at both SV breakpoints, local split read contig evidence observed.
2. Medium level of evidence: eg discordant pair signature (both breakpoints) and soft clipping signature
3. Lower level of evidence eg. discordant pair signature alone
4. Possible germline due to the presence of low quality control reads or evidence in the control bam from local split read alignment
5. Possible repeat region. Greater than 1000 clips identified in the region of the SV breakpoint/s.
6. Low level evidence - Soft clipping signature for one breakpoint

Unaligned soft clips:

  • Eg test_no_blat_alignment.txt
  • Reference positions that have >10 soft clipped reads that do not align to the reference genome and are potentially somatic
  • Tab delimited text file format with columns:
    • reference
    • position
    • mutation_type (somatic)
    • clip_type
    • left: clips on the left end of read
    • right: clips on the right end of the read
    • pos_clips
    • number of clipped reads that align to the positive strand of the reference
    • neg_clips
    • number of clipped reads that align to the negative strand of the reference
    • consensus
    • consensus sequence for clipped reads

Verbose output for structural variants.

  • Eg. test.chr10.somatic.records
  • Text file that gives information about the discordant pair reads and/or soft clipped reads that support a particular structural variant
  • Each structural variant is described by:
    • a header specifying the sv_id, and mutation type call
  • A list of the discordant reads (where appropriate) supporting the SV in the format:
    • Comma separated list of mate 1 read name:read group id, mate 1 reference, mate 1 position start, mate 1 position end, mate 1 flags, mate 1 strand, mate 2 read name:read group id, mate 2 reference, mate 2 position start, mate 2 position end, mate 2 flags, mate 2 strand, pair orientation (eg. F1R2), mutation type eg DEL/ITX based on expected read strand, orientation and distance.
  • A list of soft clipped reads (where appropriate) supporting the SV in the format:
    • Comma separated list of read name: read group id, reference, position, strand, left/right clip type, clipping sequence

Examples

Sample example files are provided here: <todo>Image Qsv Example Files</todo>
Edit the following ini file options in example.ini:

  • output: location where the results will be written
  • input_file: (test section): location of example.test.bam file
  • input_file (control section): location of example.control.bam
  • blatserver: name of blat server eg localhost
  • blatpath: path to blat software
  • blatport: port of the blat server

Make sure the BLAT server dependency has been installed and is running.
Run qSV using the following command:

java –jar qsv-0.3.jar –ini example.ini –tmp [path/to/tmp/directory]

Results will be written to the specified output directory and can be found under the directory:

  • qSV_sample name_analysis date_analysis time
  • eg qSV_PatientA_20130202_1514

References

  1. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, et al. (2009) The Sequence Alignment/Map format and SAMtools. Bioinformatics 25: 2078–2079

Related

Discussion: general
Wiki: qProfiler

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