QualifyMissingIntervals

Collect quality metrics for a set of intervals

Category Diagnostics and Quality Control Tools

Traversal LocusWalker

PartitionBy INTERVAL


Overview

This tool collects the following metrics:

  • Average Base Quality
  • Average Mapping Quality
  • Average Depth
  • GC Content
  • Position in the target (Integer.MIN_VALUE if no overlap)
  • Length of the overlapping target (zero if no overlap)
  • Coding Sequence / Intron (optional)
  • Length of the uncovered interval

It is meant to be run on a set of intervals that have been identified as problematic in earlier stages of quality control and are considered "missing" from the sequence dataset.

Input

A reference file (for GC content), the input bam file (for base and mapping quality calculation), the missing intervals (in the -L), the baits/targets used to sequence (in the -targets) and a bed file with the coding sequence intervals of the genome (in the -cds).

Output

GC content, distance from the end of the target, coding sequence intersection, mapping and base quality averages and average depth per "missing" interval.

Usage example

 java -jar GenomeAnalysisTK.jar \
   -T QualifyMissingIntervals \
   -R reference.fasta \
   -I input.bam \
   -o output.grp \
   -L input.intervals \
   -cds cds.intervals \
   -targets targets.intervals
 

Additional Information

Read filters

These Read Filters are automatically applied to the data by the Engine before processing by QualifyMissingIntervals.

Parallelism options

This tool can be run in multi-threaded mode using this option.

Downsampling settings

This tool applies the following downsampling settings by default.

  • Mode: BY_SAMPLE
  • To coverage: 1,000

Command-line Arguments

Engine arguments

All tools inherit arguments from the GATK Engine' "CommandLineGATK" argument collection, which can be used to modify various aspects of the tool's function. For example, the -L argument directs the GATK engine to restrict processing to specific genomic intervals; or the -rf argument allows you to apply certain read filters to exclude some of the data from the analysis.

QualifyMissingIntervals specific arguments

This table summarizes the command-line arguments that are specific to this tool. For more details on each argument, see the list further down below the table or click on an argument name to jump directly to that entry in the list.

Argument name(s) Default value Summary
Required Parameters
--targetsfile
 -targets
NA Undocumented option
Optional Outputs
--out
 -o
stdout An output file created by the walker. Will overwrite contents if file exists
Optional Parameters
--baitsfile
 -baits
NA Undocumented option
--coveragethreshold
 -cov
20 minimum coverage to be considered sequenceable
--gcthreshold
 -gc
0.3 upper and lower bound for an interval to be considered high/low GC content
--intervalsizethreshold
 -size
10 minimum interval length to be considered
--mappingthreshold
 -mmq
20 minimum mapping quality for it to be considered usable
--qualthreshold
 -mbq
20 minimum base quality for it to be considered usable

Argument details

Arguments in this list are specific to this tool. Keep in mind that other arguments are available that are shared with other tools (e.g. command-line GATK arguments); see Inherited arguments above.


--baitsfile / -baits

Undocumented option
List of baits to distinguish untargeted intervals from those that are targeted but not covered

String  NA


--coveragethreshold / -cov

minimum coverage to be considered sequenceable
The coverage of a missing interval may determine whether or not an interval is sequenceable. A low coverage will trigger gc content, mapping, base qualities and other checks to figure out why this interval was deemed unsequenceable.

int  20  [ [ -∞  ∞ ] ]


--gcthreshold / -gc

upper and lower bound for an interval to be considered high/low GC content
This value will be used to determine whether or not an interval had too high or too low GC content to be sequenced. This is only applied if there was not enough data in the interval.

double  0.3  [ [ -∞  ∞ ] ]


--intervalsizethreshold / -size

minimum interval length to be considered
Intervals that are too small generate biased analysis. For example an interval of size 1 will have GC content 1 or 0. To avoid misinterpreting small intervals, all intervals below this threshold will be ignored in the interpretation.

byte  10  [ [ -∞  ∞ ] ]


--mappingthreshold / -mmq

minimum mapping quality for it to be considered usable
An average mapping quality above this value will determine the interval to be mappable.

byte  20  [ [ -∞  ∞ ] ]


--out / -o

An output file created by the walker. Will overwrite contents if file exists
A single GATKReport table with the qualifications on why the intervals passed by the -L argument were missing.

PrintStream  stdout


--qualthreshold / -mbq

minimum base quality for it to be considered usable
An average base quality above this value will rule out the possibility of context specific problems with the sequencer.

byte  20  [ [ -∞  ∞ ] ]


--targetsfile / -targets

Undocumented option
List of targets used in the experiment. This file will be used to calculate the distance your missing intervals are to the targets (usually exons). Typically this is your hybrid selection targets file (e.g. Agilent exome target list)

R String  NA


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GATK version 3.8-0-ge9d806836 built at 2017/07/29 01:40:22.