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bwa.txt
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bwa(1) Bioinformatics tools bwa(1)
NAME
bwa - Burrows-Wheeler Alignment Tool
SYNOPSIS
bwa index -a bwtsw database.fasta
bwa aln database.fasta short_read.fastq > aln_sa.sai
bwa samse database.fasta aln_sa.sai short_read.fastq > aln.sam
bwa sampe database.fasta aln_sa1.sai aln_sa2.sai read1.fq read2.fq >
aln.sam
bwa bwasw database.fasta long_read.fastq > aln.sam
DESCRIPTION
BWA is a fast light-weighted tool that aligns relatively short
sequences (queries) to a sequence database (targe), such as the human
reference genome. It implements two different algorithms, both based on
Burrows-Wheeler Transform (BWT). The first algorithm is designed for
short queries up to ~150bp with low error rate (<3%). It does gapped
global alignment w.r.t. queries, supports paired-end reads, and is one
of the fastest short read alignment algorithms to date while also vis-
iting suboptimal hits. The second algorithm, BWA-SW, is designed for
reads longer than 100bp with more errors. It performs a heuristic
Smith-Waterman-like alignment to find high-scoring local hits and split
hits. On low-error short queries, BWA-SW is a little slower and less
accurate than the first algorithm, but on long queries, it is better.
For both algorithms, the database file in the FASTA format must be
first indexed with the `index' command, which typically takes a few
hours for a 3GB genome. The first algorithm is implemented via the
`aln' command, which finds the suffix array (SA) coordinates of good
hits of each individual read, and the `samse/sampe' command, which con-
verts SA coordinates to chromosomal coordinate and pairs reads (for
`sampe'). The second algorithm is invoked by the `bwasw' command. It
works for single-end reads only.
COMMANDS AND OPTIONS
index bwa index [-p prefix] [-a algoType] <in.db.fasta>
Index database sequences in the FASTA format.
OPTIONS:
-c Build color-space index. The input fast should be in
nucleotide space. (Disabled since 0.6.x)
-p STR Prefix of the output database [same as db filename]
-a STR Algorithm for constructing BWT index. Available
options are:
is IS linear-time algorithm for constructing suf-
fix array. It requires 5.37N memory where N is
the size of the database. IS is moderately
fast, but does not work with database larger
than 2GB. IS is the default algorithm due to
its simplicity. The current codes for IS algo-
rithm are reimplemented by Yuta Mori.
bwtsw Algorithm implemented in BWT-SW. This method
works with the whole human genome.
aln bwa aln [-n maxDiff] [-o maxGapO] [-e maxGapE] [-d nDelTail] [-i
nIndelEnd] [-k maxSeedDiff] [-l seedLen] [-t nThrds] [-cRN] [-M
misMsc] [-O gapOsc] [-E gapEsc] [-q trimQual] <in.db.fasta>
<in.query.fq> > <out.sai>
Find the SA coordinates of the input reads. Maximum maxSeedDiff
differences are allowed in the first seedLen subsequence and
maximum maxDiff differences are allowed in the whole sequence.
OPTIONS:
-n NUM Maximum edit distance if the value is INT, or the
fraction of missing alignments given 2% uniform base
error rate if FLOAT. In the latter case, the maximum
edit distance is automatically chosen for different
read lengths. [0.04]
-o INT Maximum number of gap opens [1]
-e INT Maximum number of gap extensions, -1 for k-difference
mode (disallowing long gaps) [-1]
-d INT Disallow a long deletion within INT bp towards the
3'-end [16]
-i INT Disallow an indel within INT bp towards the ends [5]
-l INT Take the first INT subsequence as seed. If INT is
larger than the query sequence, seeding will be dis-
abled. For long reads, this option is typically ranged
from 25 to 35 for `-k 2'. [inf]
-k INT Maximum edit distance in the seed [2]
-t INT Number of threads (multi-threading mode) [1]
-M INT Mismatch penalty. BWA will not search for suboptimal
hits with a score lower than (bestScore-misMsc). [3]
-O INT Gap open penalty [11]
-E INT Gap extension penalty [4]
-R INT Proceed with suboptimal alignments if there are no
more than INT equally best hits. This option only
affects paired-end mapping. Increasing this threshold
helps to improve the pairing accuracy at the cost of
speed, especially for short reads (~32bp).
-c Reverse query but not complement it, which is required
for alignment in the color space. (Disabled since
0.6.x)
-N Disable iterative search. All hits with no more than
maxDiff differences will be found. This mode is much
slower than the default.
-q INT Parameter for read trimming. BWA trims a read down to
argmax_x{\sum_{i=x+1}^l(INT-q_i)} if q_l<INT where l
is the original read length. [0]
-I The input is in the Illumina 1.3+ read format (quality
equals ASCII-64).
-B INT Length of barcode starting from the 5'-end. When INT
is positive, the barcode of each read will be trimmed
before mapping and will be written at the BC SAM tag.
For paired-end reads, the barcode from both ends are
concatenated. [0]
-b Specify the input read sequence file is the BAM for-
mat. For paired-end data, two ends in a pair must be
grouped together and options -1 or -2 are usually
applied to specify which end should be mapped. Typical
command lines for mapping pair-end data in the BAM
format are:
bwa aln ref.fa -b1 reads.bam > 1.sai
bwa aln ref.fa -b2 reads.bam > 2.sai
bwa sampe ref.fa 1.sai 2.sai reads.bam reads.bam >
aln.sam
-0 When -b is specified, only use single-end reads in
mapping.
-1 When -b is specified, only use the first read in a
read pair in mapping (skip single-end reads and the
second reads).
-2 When -b is specified, only use the second read in a
read pair in mapping.
samse bwa samse [-n maxOcc] <in.db.fasta> <in.sai> <in.fq> > <out.sam>
Generate alignments in the SAM format given single-end reads.
Repetitive hits will be randomly chosen.
OPTIONS:
-n INT Maximum number of alignments to output in the XA tag
for reads paired properly. If a read has more than INT
hits, the XA tag will not be written. [3]
-r STR Specify the read group in a format like
`@RG\tID:foo\tSM:bar'. [null]
sampe bwa sampe [-a maxInsSize] [-o maxOcc] [-n maxHitPaired] [-N max-
HitDis] [-P] <in.db.fasta> <in1.sai> <in2.sai> <in1.fq> <in2.fq>
> <out.sam>
Generate alignments in the SAM format given paired-end reads.
Repetitive read pairs will be placed randomly.
OPTIONS:
-a INT Maximum insert size for a read pair to be considered
being mapped properly. Since 0.4.5, this option is only
used when there are not enough good alignment to infer
the distribution of insert sizes. [500]
-o INT Maximum occurrences of a read for pairing. A read with
more occurrneces will be treated as a single-end read.
Reducing this parameter helps faster pairing. [100000]
-P Load the entire FM-index into memory to reduce disk
operations (base-space reads only). With this option, at
least 1.25N bytes of memory are required, where N is the
length of the genome.
-n INT Maximum number of alignments to output in the XA tag for
reads paired properly. If a read has more than INT hits,
the XA tag will not be written. [3]
-N INT Maximum number of alignments to output in the XA tag for
disconcordant read pairs (excluding singletons). If a
read has more than INT hits, the XA tag will not be
written. [10]
-r STR Specify the read group in a format like
`@RG\tID:foo\tSM:bar'. [null]
bwasw bwa bwasw [-a matchScore] [-b mmPen] [-q gapOpenPen] [-r
gapExtPen] [-t nThreads] [-w bandWidth] [-T thres] [-s hspIntv]
[-z zBest] [-N nHspRev] [-c thresCoef] <in.db.fasta> <in.fq>
[mate.fq]
Align query sequences in the in.fq file. When mate.fq is
present, perform paired-end alignment. The paired-end mode only
works for reads Illumina short-insert libraries. In the paired-
end mode, BWA-SW may still output split alignments but they are
all marked as not properly paired; the mate positions will not
be written if the mate has multiple local hits.
OPTIONS:
-a INT Score of a match [1]
-b INT Mismatch penalty [3]
-q INT Gap open penalty [5]
-r INT Gap extension penalty. The penalty for a contiguous
gap of size k is q+k*r. [2]
-t INT Number of threads in the multi-threading mode [1]
-w INT Band width in the banded alignment [33]
-T INT Minimum score threshold divided by a [37]
-c FLOAT Coefficient for threshold adjustment according to
query length. Given an l-long query, the threshold for
a hit to be retained is a*max{T,c*log(l)}. [5.5]
-z INT Z-best heuristics. Higher -z increases accuracy at the
cost of speed. [1]
-s INT Maximum SA interval size for initiating a seed. Higher
-s increases accuracy at the cost of speed. [3]
-N INT Minimum number of seeds supporting the resultant
alignment to skip reverse alignment. [5]
SAM ALIGNMENT FORMAT
The output of the `aln' command is binary and designed for BWA use
only. BWA outputs the final alignment in the SAM (Sequence Align-
ment/Map) format. Each line consists of:
+----+-------+----------------------------------------------------------+
|Col | Field | Description |
+----+-------+----------------------------------------------------------+
| 1 | QNAME | Query (pair) NAME |
| 2 | FLAG | bitwise FLAG |
| 3 | RNAME | Reference sequence NAME |
| 4 | POS | 1-based leftmost POSition/coordinate of clipped sequence |
| 5 | MAPQ | MAPping Quality (Phred-scaled) |
| 6 | CIAGR | extended CIGAR string |
| 7 | MRNM | Mate Reference sequence NaMe (`=' if same as RNAME) |
| 8 | MPOS | 1-based Mate POSistion |
| 9 | ISIZE | Inferred insert SIZE |
|10 | SEQ | query SEQuence on the same strand as the reference |
|11 | QUAL | query QUALity (ASCII-33 gives the Phred base quality) |
|12 | OPT | variable OPTional fields in the format TAG:VTYPE:VALUE |
+----+-------+----------------------------------------------------------+
Each bit in the FLAG field is defined as:
+----+--------+---------------------------------------+
|Chr | Flag | Description |
+----+--------+---------------------------------------+
| p | 0x0001 | the read is paired in sequencing |
| P | 0x0002 | the read is mapped in a proper pair |
| u | 0x0004 | the query sequence itself is unmapped |
| U | 0x0008 | the mate is unmapped |
| r | 0x0010 | strand of the query (1 for reverse) |
| R | 0x0020 | strand of the mate |
| 1 | 0x0040 | the read is the first read in a pair |
| 2 | 0x0080 | the read is the second read in a pair |
| s | 0x0100 | the alignment is not primary |
| f | 0x0200 | QC failure |
| d | 0x0400 | optical or PCR duplicate |
+----+--------+---------------------------------------+
The Please check <http://samtools.sourceforge.net> for the format spec-
ification and the tools for post-processing the alignment.
BWA generates the following optional fields. Tags starting with `X' are
specific to BWA.
+----+------------------------------------------------+
|Tag | Meaning |
+----+------------------------------------------------+
|NM | Edit distance |
|MD | Mismatching positions/bases |
|AS | Alignment score |
|BC | Barcode sequence |
+----+------------------------------------------------+
|X0 | Number of best hits |
|X1 | Number of suboptimal hits found by BWA |
|XN | Number of ambiguous bases in the referenece |
|XM | Number of mismatches in the alignment |
|XO | Number of gap opens |
|XG | Number of gap extentions |
|XT | Type: Unique/Repeat/N/Mate-sw |
|XA | Alternative hits; format: (chr,pos,CIGAR,NM;)* |
+----+------------------------------------------------+
|XS | Suboptimal alignment score |
|XF | Support from forward/reverse alignment |
|XE | Number of supporting seeds |
+----+------------------------------------------------+
Note that XO and XG are generated by BWT search while the CIGAR string
by Smith-Waterman alignment. These two tags may be inconsistent with
the CIGAR string. This is not a bug.
NOTES ON SHORT-READ ALIGNMENT
Alignment Accuracy
When seeding is disabled, BWA guarantees to find an alignment contain-
ing maximum maxDiff differences including maxGapO gap opens which do
not occur within nIndelEnd bp towards either end of the query. Longer
gaps may be found if maxGapE is positive, but it is not guaranteed to
find all hits. When seeding is enabled, BWA further requires that the
first seedLen subsequence contains no more than maxSeedDiff differ-
ences.
When gapped alignment is disabled, BWA is expected to generate the same
alignment as Eland version 1, the Illumina alignment program. However,
as BWA change `N' in the database sequence to random nucleotides, hits
to these random sequences will also be counted. As a consequence, BWA
may mark a unique hit as a repeat, if the random sequences happen to be
identical to the sequences which should be unqiue in the database.
By default, if the best hit is not highly repetitive (controlled by
-R), BWA also finds all hits contains one more mismatch; otherwise, BWA
finds all equally best hits only. Base quality is NOT considered in
evaluating hits. In the paired-end mode, BWA pairs all hits it found.
It further performs Smith-Waterman alignment for unmapped reads to res-
cue reads with a high erro rate, and for high-quality anomalous pairs
to fix potential alignment errors.
Estimating Insert Size Distribution
BWA estimates the insert size distribution per 256*1024 read pairs. It
first collects pairs of reads with both ends mapped with a single-end
quality 20 or higher and then calculates median (Q2), lower and higher
quartile (Q1 and Q3). It estimates the mean and the variance of the
insert size distribution from pairs whose insert sizes are within
interval [Q1-2(Q3-Q1), Q3+2(Q3-Q1)]. The maximum distance x for a pair
considered to be properly paired (SAM flag 0x2) is calculated by solv-
ing equation Phi((x-mu)/sigma)=x/L*p0, where mu is the mean, sigma is
the standard error of the insert size distribution, L is the length of
the genome, p0 is prior of anomalous pair and Phi() is the standard
cumulative distribution function. For mapping Illumina short-insert
reads to the human genome, x is about 6-7 sigma away from the mean.
Quartiles, mean, variance and x will be printed to the standard error
output.
Memory Requirement
With bwtsw algorithm, 5GB memory is required for indexing the complete
human genome sequences. For short reads, the aln command uses ~3.2GB
memory and the sampe command uses ~5.4GB.
Speed
Indexing the human genome sequences takes 3 hours with bwtsw algorithm.
Indexing smaller genomes with IS algorithms is faster, but requires
more memory.
The speed of alignment is largely determined by the error rate of the
query sequences (r). Firstly, BWA runs much faster for near perfect
hits than for hits with many differences, and it stops searching for a
hit with l+2 differences if a l-difference hit is found. This means BWA
will be very slow if r is high because in this case BWA has to visit
hits with many differences and looking for these hits is expensive.
Secondly, the alignment algorithm behind makes the speed sensitive to
[k log(N)/m], where k is the maximum allowed differences, N the size of
database and m the length of a query. In practice, we choose k w.r.t. r
and therefore r is the leading factor. I would not recommend to use BWA
on data with r>0.02.
Pairing is slower for shorter reads. This is mainly because shorter
reads have more spurious hits and converting SA coordinates to chromo-
somal coordinates are very costly.
NOTES ON LONG-READ ALIGNMENT
Command bwasw is designed for long-read alignment. BWA-SW essentially
aligns the trie of the reference genome against the directed acyclic
word graph (DAWG) of a read to find seeds not highly repetitive in the
genome, and then performs a standard Smith-Waterman algorithm to extend
the seeds. A key heuristic, called the Z-best heuristic, is that at
each vertex in the DAWG, BWA-SW only keeps the top Z reference suffix
intervals that match the vertex. BWA-SW is more accurate if the resul-
tant alignment is supported by more seeds, and therefore BWA-SW usually
performs better on long queries or queries with low divergence to the
reference genome.
BWA-SW is perhaps a better choice than BWA-short for 100bp single-end
HiSeq reads mainly because it gives better gapped alignment. For
paired-end reads, it is yet to know whether BWA-short or BWA-SW yield
overall better results.
CHANGES IN BWA-0.6
Since version 0.6, BWA has been able to work with a reference genome
longer than 4GB. This feature makes it possible to integrate the for-
ward and reverse complemented genome in one FM-index, which speeds up
both BWA-short and BWA-SW. As a tradeoff, BWA uses more memory because
it has to keep all positions and ranks in 64-bit integers, twice larger
than 32-bit integers used in the previous versions.
The latest BWA-SW also works for paired-end reads longer than 100bp. In
comparison to BWA-short, BWA-SW tends to be more accurate for highly
unique reads and more robust to relative long INDELs and structural
variants. Nonetheless, BWA-short usually has higher power to distin-
guish the optimal hit from many suboptimal hits. The choice of the map-
ping algorithm may depend on the application.
SEE ALSO
BWA website <http://bio-bwa.sourceforge.net>, Samtools website
<http://samtools.sourceforge.net>
AUTHOR
Heng Li at the Sanger Institute wrote the key source codes and inte-
grated the following codes for BWT construction: bwtsw
<http://i.cs.hku.hk/~ckwong3/bwtsw/>, implemented by Chi-Kwong Wong at
the University of Hong Kong and IS
<http://yuta.256.googlepages.com/sais> originally proposed by Nong Ge
<http://www.cs.sysu.edu.cn/nong/> at the Sun Yat-Sen University and
implemented by Yuta Mori.
LICENSE AND CITATION
The full BWA package is distributed under GPLv3 as it uses source codes
from BWT-SW which is covered by GPL. Sorting, hash table, BWT and IS
libraries are distributed under the MIT license.
If you use the short-read alignment component, please cite the follow-
ing paper:
Li H. and Durbin R. (2009) Fast and accurate short read alignment with
Burrows-Wheeler transform. Bioinformatics, 25, 1754-1760. [PMID:
19451168]
If you use the long-read component (BWA-SW), please cite:
Li H. and Durbin R. (2010) Fast and accurate long-read alignment with
Burrows-Wheeler transform. Bioinformatics, 26, 589-595. [PMID:
20080505]
HISTORY
BWA is largely influenced by BWT-SW. It uses source codes from BWT-SW
and mimics its binary file formats; BWA-SW resembles BWT-SW in several
ways. The initial idea about BWT-based alignment also came from the
group who developed BWT-SW. At the same time, BWA is different enough
from BWT-SW. The short-read alignment algorithm bears no similarity to
Smith-Waterman algorithm any more. While BWA-SW learns from BWT-SW, it
introduces heuristics that can hardly be applied to the original algo-
rithm. In all, BWA does not guarantee to find all local hits as what
BWT-SW is designed to do, but it is much faster than BWT-SW on both
short and long query sequences.
I started to write the first piece of codes on 24 May 2008 and got the
initial stable version on 02 June 2008. During this period, I was
acquainted that Professor Tak-Wah Lam, the first author of BWT-SW
paper, was collaborating with Beijing Genomics Institute on SOAP2, the
successor to SOAP (Short Oligonucleotide Analysis Package). SOAP2 has
come out in November 2008. According to the SourceForge download page,
the third BWT-based short read aligner, bowtie, was first released in
August 2008. At the time of writing this manual, at least three more
BWT-based short-read aligners are being implemented.
The BWA-SW algorithm is a new component of BWA. It was conceived in
November 2008 and implemented ten months later.
bwa-0.6.1 28 November 2011 bwa(1)