Classify PF-Failing reads in a HiSeqX Illumina Basecalling directory into various categories.
This tool categorizes the reads that did not pass filter (PF-Failing) into four groups. These groups are based on a heuristic that was derived by looking at a few titration experiments.
After examining the called bases from the first 24 cycles of each read, the PF-Failed reads are grouped into the following four categories:
- MISALIGNED - The first 24 basecalls of a read are uncalled (numNs~24). These types of reads appear to be flow cell artifacts because reads were only found near tile boundaries and were concentration (library) independent
- EMPTY - All 24 bases are called (numNs~0) but the number of bases with quality scores greater than two is less than or equal to eight (numQGtTwo<=8). These reads were location independent within the tiles and were inversely proportional to the library concentration
- POLYCLONAL - All 24 bases were called and numQGtTwo>=12, were independent of their location with the tiles, and were directly proportional to the library concentration. These reads are likely the result of PCR artifacts
- UNKNOWN - The remaining reads that are PF-Failing but did not fit into any of the groups listed above
The tool defaults to the SUMMARY output which indicates the number of PF-Failed reads per tile and groups them into the categories described above accordingly.
A DETAILED metrics option is also available that subdivides the SUMMARY outputs by the x- y- position of these reads within each tile. To obtain the DETAILED metric table, you must add the PROB_EXPLICIT_READS option to your command line and set the value between 0 and 1. This value represents the fractional probability of PF-Failed reads to send to output. For example, if PROB_EXPLICIT_READS=0, then no metrics will be output. If PROB_EXPLICIT_READS=1, then it will provide detailed metrics for all (100%) of the reads. It follows that setting the PROB_EXPLICIT_READS=0.5, will provide detailed metrics for half of the PF-Failed reads.
Note: Metrics labeled as percentages are actually expressed as fractions!
Usage example: (SUMMARY Metrics)
java -jar picard.jar CollectHiSeqXPfFailMetrics \
Usage example: (DETAILED Metrics)
java -jar picard.jar CollectHiSeqXPfFailMetrics \Please see our documentation on the SUMMARY and DETAILED metrics for comprehensive explanations of the outputs produced by this tool.
Category Diagnostics and Quality Control
OverviewCollect metrics regarding the reason for reads (sequenced by HiSeqX) not passing the Illumina PF Filter. (BETA)
CollectHiSeqXPfFailMetrics (Picard) 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|
|The Illumina basecalls directory.|
|Basename for metrics file. Resulting file will be|
|Optional Tool Arguments|
||read one or more arguments files and add them to the command line|
|false||display the help message|
||24||Number of cycles to look at. At time of writing PF status gets determined at cycle 24 so numbers greater than this will yield strange results. In addition, PF status is currently determined at cycle 24, so running this with any other value is neither tested nor recommended.|
|1||Run this many PerTileBarcodeExtractors in parallel. If NUM_PROCESSORS = 0, number of cores is automatically set to the number of cores available on the machine. If NUM_PROCESSORS < 0 then the number of cores used will be the number available on the machine less NUM_PROCESSORS.|
|0.0||The fraction of (non-PF) reads for which to output explicit classification. Output file will be|
||false||display the version number for this tool|
|Optional Common Arguments|
||5||Compression level for all compressed files created (e.g. BAM and VCF).|
||false||Whether to create an index when writing VCF or coordinate sorted BAM output.|
||false||Whether to create an MD5 digest for any BAM or FASTQ files created.|
||client_secrets.json||Google Genomics API client_secrets.json file path.|
||500000||When writing files that need to be sorted, this will specify the number of records stored in RAM before spilling to disk. Increasing this number reduces the number of file handles needed to sort the file, and increases the amount of RAM needed.|
||false||Whether to suppress job-summary info on System.err.|
|Reference sequence file.|
||One or more directories with space available to be used by this program for temporary storage of working files|
|false||Use the JDK Deflater instead of the Intel Deflater for writing compressed output|
|false||Use the JDK Inflater instead of the Intel Inflater for reading compressed input|
||STRICT||Validation stringency for all SAM files read by this program. Setting stringency to SILENT can improve performance when processing a BAM file in which variable-length data (read, qualities, tags) do not otherwise need to be decoded.|
||INFO||Control verbosity of logging.|
||false||display hidden arguments|
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.
read one or more arguments files and add them to the command line
--BASECALLS_DIR / -B
The Illumina basecalls directory.
R File null
Compression level for all compressed files created (e.g. BAM and VCF).
int 5 [ [ -∞ ∞ ] ]
Whether to create an index when writing VCF or coordinate sorted BAM output.
Whether to create an MD5 digest for any BAM or FASTQ files created.
Google Genomics API client_secrets.json file path.
--help / -h
display the help message
--LANE / -L
R Integer null
Integer 500000 [ [ -∞ ∞ ] ]
Number of cycles to look at. At time of writing PF status gets determined at cycle 24 so numbers greater than this will yield strange results. In addition, PF status is currently determined at cycle 24, so running this with any other value is neither tested nor recommended.
int 24 [ [ -∞ ∞ ] ]
--NUM_PROCESSORS / -NP
int 1 [ [ -∞ ∞ ] ]
--OUTPUT / -O
Basename for metrics file. Resulting file will be
R File null
The fraction of (non-PF) reads for which to output explicit classification. Output file will be
double 0.0 [ [ -∞ ∞ ] ]
Whether to suppress job-summary info on System.err.
--REFERENCE_SEQUENCE / -R
Reference sequence file.
--showHidden / -showHidden
display hidden arguments
--USE_JDK_DEFLATER / -use_jdk_deflater
Use the JDK Deflater instead of the Intel Deflater for writing compressed output
--USE_JDK_INFLATER / -use_jdk_inflater
Use the JDK Inflater instead of the Intel Inflater for reading compressed input
The --VALIDATION_STRINGENCY argument is an enumerated type (ValidationStringency), which can have one of the following values:
Control verbosity of logging.
The --VERBOSITY argument is an enumerated type (LogLevel), which can have one of the following values:
display the version number for this tool
GATK version 220.127.116.11-SNAPSHOT built at Mon, 19 Oct 2020 11:41:12 -0400.