samtools markdup [-l length] [-r] [-T] [-S] [-s] [-f file] [--json] [-d distance] [-c] [-t] [---duplicate-count] [-m] [--mode] [--include-fails] [--no-PG] [-u] [--no-multi-dup] [--read-coords] [--coords-order] [--barcode-tag] [--barcode-name] [--barcode-rgx] [--use-read-groups] in.algsort.bam out.bam
Mark duplicate alignments from a coordinate sorted file that has been run through samtools fixmate with the -m option. This program relies on the MC and ms tags that fixmate provides.
Duplicates are found by using the alignment data for each read (and its mate for paired reads). Position and orientation (which strand it aligns against and in what direction) are used to to compare the reads against one another. If two (or more) reads have the same values then the one with the highest base qualities is held to be the original and the others are the duplicates.
It should be noted that samtools markdup looks for duplication first and then classifies the type of duplication afterwards. If your process does not care whether duplication is PCR or optical then it is faster if you do not use the optical duplicate option.
Duplicates are marked by setting the alignment's DUP flag.
For more details please see:
<http://www.htslib.org/algorithms/duplicate.html>
Expected maximum read length of INT bases. [300]
Remove duplicate reads.
Write temporary files to PREFIX.samtools.nnnn.mmmm.tmp
Mark supplementary reads of duplicates as duplicates.
Print some basic stats. See STATISTICS.
Write stats to named file.
Output stats in JSON format.
The optical duplicate distance. Suggested settings of 100 for HiSeq style platforms or about 2500 for NovaSeq ones. Default is 0 to not look for optical duplicates. When set, duplicate reads are tagged with dt:Z:SQ for optical duplicates and dt:Z:LB otherwise. Calculation of distance depends on coordinate data embedded in the read names produced by the Illumina sequencing machines. Optical duplicate detection will not work on non standard names without the use of --read-coords.
Clear previous duplicate settings and tags.
Mark duplicates with the name of the original in a do tag.
Record the original primary read duplication count (including itself) in a dc tag.
Duplicate decision method for paired reads. Values are t or s. Mode t measures positions based on template start/end (default). Mode s measures positions based on sequence start. While the two methods identify mostly the same reads as duplicates, mode s tends to return more results. Unpaired reads are treated identically by both modes.
Output uncompressed SAM, BAM or CRAM.
Include quality checked failed reads.
Stop checking duplicates of duplicates for correctness. While still marking reads as duplicates further checks to make sure all optical duplicates are found are not carried out. Also operates on -t tagging where reads may tagged with a better quality read but not necessarily the best one. Using this option can speed up duplicate marking when there are a great many duplicates for each original read.
This takes a POSIX regular expression for at least x and y to be used in optical duplicate marking It can also include another part of the read name to test for equality, eg lane:tile elements. Elements wanted are captured with parentheses. Examples below.
The order of the elements captured in the regular expression. Default is txy where t is a part of the read name selected for string comparison and x/y the coordinates used for optical duplicate detection. Valid orders are: txy, tyx, xyt, yxt, xty, ytx, xy and yx.
Duplicates must now also match the barcode tag.
Use the UMI/barcode embedded in the read name (eigth colon delimited part).
Regex for barcode in the readname (alternative to --barcode-name).
The @RG tags must now also match to be a duplicate.
Do not add a PG line to the output file.
Number of input/output compression threads to use in addition to main thread [0].
Estimated library size makes various assumptions e.g. the library consists of unique fragments that are randomly selected (with replacement) with equal probability. This is unlikely to be true in practice. However it can provide a useful guide into how many unique read pairs are likely to be available. In particular it can be used to determine how much more data might be obtained by further sequencing of the library.
Excluded reads are those marked as secondary, supplementary or unmapped. By default QC failed reads are also excluded but can be included as an option. Excluded reads are not used for calculating duplicates. They can optionally be marked as duplicates if they have a primary that is also a duplicate.
samtools collate -o namecollate.bam example.bam
Add ms and MC tags for markdup to use later:
samtools fixmate -m namecollate.bam fixmate.bam
Markdup needs position order:
samtools sort -o positionsort.bam fixmate.bam
Finally mark duplicates:
samtools markdup positionsort.bam markdup.bam
Typically the fixmate step would be applied immediately after sequence alignment and the markdup step after sorting by chromosome and position. Thus no additional sort steps are normally needed.
To use the regex to obtain coordinates from reads, two or three values have to be captured. To mimic the normal behaviour and match a read name of the format machine:run:flowcell:lane:tile:x:y use:
--read-coords '([!-9;-?A-~]+:[0-9]+:[0-9]+:[0-9]+:[0-9]+):([0-9]+):([0-9]+)' --coords-order txy
To match only the coordinates of x:y:randomstuff use:
--read-coords '^([[:digit:]]+):([[:digit:]]+)' --coords-order xy
To use a barcode from the read name matching the Illumina example of NDX550136:7:H2MTNBDXX:1:13302:3141:10799:AAGGATG+TCGGAGA use:
--barcode-rgx '[0-9A-Za-z]+:[0-9]+:[0-9A-Za-z]+:[0-9]+:[0-9]+:[0-9]+:[0-9]+:([!-?A-~]+)'
It is possible that complex regular expressions may slow the running of the program. It would be best to keep them simple.
Written by Andrew Whitwham from the Sanger Institute.
Samtools website: <http://www.htslib.org/>
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