bwa(1) Bioinformatics tools bwa(1)NAMEbwa - Burrows-Wheeler Alignment Tool
SYNOPSISbwa index ref.fa
bwa mem ref.fa reads.fq > aln-se.sam
bwa mem ref.fa read1.fq read2.fq > aln-pe.sam
bwa aln ref.fa short_read.fq > aln_sa.sai
bwa samse ref.fa aln_sa.sai short_read.fq > aln-se.sam
bwa sampe ref.fa aln_sa1.sai aln_sa2.sai read1.fq read2.fq > aln-pe.sam
bwa bwasw ref.fa long_read.fq > aln.sam
DESCRIPTION
BWA is a software package for mapping low-divergent sequences against a
large reference genome, such as the human genome. It consists of three
algorithms: BWA-backtrack, BWA-SW and BWA-MEM. The first algorithm is
designed for Illumina sequence reads up to 100bp, while the rest two
for longer sequences ranged from 70bp to 1Mbp. BWA-MEM and BWA-SW share
similar features such as long-read support and split alignment, but
BWA-MEM, which is the latest, is generally recommended for high-quality
queries as it is faster and more accurate. BWA-MEM also has better
performance than BWA-backtrack for 70-100bp Illumina reads.
For all the algorithms, BWA first needs to construct the FM-index for
the reference genome (the index command). Alignment algorithms are
invoked with different sub-commands: aln/samse/sampe for BWA-backtrack,
bwasw for BWA-SW and mem for the BWA-MEM algorithm.
COMMANDS AND OPTIONS
index bwa index [-p prefix] [-a algoType] db.fa
Index database sequences in the FASTA format.
OPTIONS:
-p STR Prefix of the output database [same as db filename]
-a STR Algorithm for constructing BWT index. BWA implements
two algorithms for BWT construction: is and bwtsw.
The first algorithm is a little faster for small data‐
base but requires large RAM and does not work for
databases with total length longer than 2GB. The sec‐
ond algorithm is adapted from the BWT-SW source code.
It in theory works with database with trillions of
bases. When this option is not specified, the appro‐
priate algorithm will be chosen automatically.
mem bwa mem [-aCHMpP] [-t nThreads] [-k minSeedLen] [-w bandWidth]
[-d zDropoff] [-r seedSplitRatio] [-c maxOcc] [-A matchScore]
[-B mmPenalty] [-O gapOpenPen] [-E gapExtPen] [-L clipPen] [-U
unpairPen] [-R RGline] [-v verboseLevel] db.prefix reads.fq
[mates.fq]
Align 70bp-1Mbp query sequences with the BWA-MEM algorithm.
Briefly, the algorithm works by seeding alignments with maximal
exact matches (MEMs) and then extending seeds with the affine-
gap Smith-Waterman algorithm (SW).
If mates.fq file is absent and option -p is not set, this com‐
mand regards input reads are single-end. If mates.fq is present,
this command assumes the i-th read in reads.fq and the i-th read
in mates.fq constitute a read pair. If -p is used, the command
assumes the 2i-th and the (2i+1)-th read in reads.fq constitute
a read pair (such input file is said to be interleaved). In this
case, mates.fq is ignored. In the paired-end mode, the mem com‐
mand will infer the read orientation and the insert size distri‐
bution from a batch of reads.
The BWA-MEM algorithm performs local alignment. It may produce
multiple primary alignments for different part of a query
sequence. This is a crucial feature for long sequences. However,
some tools such as Picard's markDuplicates does not work with
split alignments. One may consider to use option -M to flag
shorter split hits as secondary.
ALGORITHM OPTIONS:
-t INT Number of threads [1]
-k INT Minimum seed length. Matches shorter than INT will be
missed. The alignment speed is usually insensitive to
this value unless it significantly deviates from 20.
[19]
-w INT Band width. Essentially, gaps longer than INT will not
be found. Note that the maximum gap length is also
affected by the scoring matrix and the hit length, not
solely determined by this option. [100]
-d INT Off-diagonal X-dropoff (Z-dropoff). Stop extension
when the difference between the best and the current
extension score is above |i-j|*A+INT, where i and j
are the current positions of the query and reference,
respectively, and A is the matching score. Z-dropoff
is similar to BLAST's X-dropoff except that it doesn't
penalize gaps in one of the sequences in the align‐
ment. Z-dropoff not only avoids unnecessary extension,
but also reduces poor alignments inside a long good
alignment. [100]
-r FLOAT Trigger re-seeding for a MEM longer than min‐
SeedLen*FLOAT. This is a key heuristic parameter for
tuning the performance. Larger value yields fewer
seeds, which leads to faster alignment speed but lower
accuracy. [1.5]
-c INT Discard a MEM if it has more than INT occurence in the
genome. This is an insensitive parameter. [500]
-P In the paired-end mode, perform SW to rescue missing
hits only but do not try to find hits that fit a
proper pair.
-A INT Matching score. [1]
-B INT Mismatch penalty. The sequence error rate is approxi‐
mately: {.75 * exp[-log(4) * B/A]}. [4]
-O INT[,INT]
Gap open penalty. If two numbers are specified, the
first is the penalty of openning a deletion and the
second for openning an insertion. [6]
-E INT[,INT]
Gap extension penalty. If two numbers are specified,
the first is the penalty of extending a deletion and
second for extending an insertion. A gap of length k
costs O + k*E (i.e. -O is for opening a zero-length
gap). [1]
-L INT[,INT]
Clipping penalty. When performing SW extension, BWA-
MEM keeps track of the best score reaching the end of
query. If this score is larger than the best SW score
minus the clipping penalty, clipping will not be
applied. Note that in this case, the SAM AS tag
reports the best SW score; clipping penalty is not
deduced. If two numbers are provided, the first is for
5'-end clipping and second for 3'-end clipping. [5]
-U INT Penalty for an unpaired read pair. BWA-MEM scores an
unpaired read pair as scoreRead1+scoreRead2-INT and
scores a paired as scoreRead1+scoreRead2-insert‐
Penalty. It compares these two scores to determine
whether we should force pairing. A larger value leads
to more aggressive read pair. [17]
INPUT/OUTPUT OPTIONS:
-p Assume the first input query file is interleaved
paired-end FASTA/Q. See the command description for
details.
-R STR Complete read group header line. '\t' can be used in
STR and will be converted to a TAB in the output SAM.
The read group ID will be attached to every read in
the output. An example is '@RG\tID:foo\tSM:bar'.
[null]
-T INT Don't output alignment with score lower than INT.
This option affects output and occasionally SAM flag
2. [30]
-h INT If a query has not more than INT hits with score
higher than 80% of the best hit, output them all in
the XA tag [5]
-a Output all found alignments for single-end or unpaired
paired-end reads. These alignments will be flagged as
secondary alignments.
-C Append append FASTA/Q comment to SAM output. This
option can be used to transfer read meta information
(e.g. barcode) to the SAM output. Note that the
FASTA/Q comment (the string after a space in the
header line) must conform the SAM spec (e.g.
BC:Z:CGTAC). Malformated comments lead to incorrect
SAM output.
-Y Use soft clipping CIGAR operation for supplementary
alignments. By default, BWA-MEM uses soft clipping for
the primary alignment and hard clipping for supplemen‐
tary alignments.
-M Mark shorter split hits as secondary (for Picard com‐
patibility).
-v INT Control the verbose level of the output. This option
has not been fully supported throughout BWA. Ideally,
a value 0 for disabling all the output to stderr; 1
for outputting errors only; 2 for warnings and errors;
3 for all normal messages; 4 or higher for debugging.
When this option takes value 4, the output is not SAM.
[3]
-I FLOAT[,FLOAT[,INT[,INT]]]
Specify the mean, standard deviation (10% of the mean
if absent), max (4 sigma from the mean if absent) and
min (4 sigma if absent) of the insert size distribu‐
tion. Only applicable to the FR orientation. By
default, BWA-MEM infers these numbers and the pair
orientations given enough reads. [inferred]
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 │
│SA │ Supplementary alignments │
├────┼───────────────────────────────────────────────────────┤
│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 │
├────┼───────────────────────────────────────────────────────┤
│XP │ Alt primary hits; format: /(chr,pos,CIGAR,mapQ,NM;)+/ │
└────┴───────────────────────────────────────────────────────┘
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.
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 BWA-backtrack algorithm, please cite the following
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 BWA-SW algorithm, please cite:
Li H. and Durbin R. (2010) Fast and accurate long-read alignment with
Burrows-Wheeler transform. Bioinformatics, 26, 589-595. [PMID:
20080505]
If you use BWA-MEM or the fastmap component of BWA, please cite:
Li H. (2013) Aligning sequence reads, clone sequences and assembly con‐
tigs with BWA-MEM. arXiv:1303.3997v1 [q-bio.GN].
It is likely that the BWA-MEM manuscript will not appear in a peer-
reviewed journal.
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 No‐
vember 2008 and implemented ten months later.
The BWA-MEM algorithm is based on an algorithm finding super-maximal
exact matches (SMEMs), which was first published with the fermi assem‐
bler paper in 2012. I first implemented the basic SMEM algorithm in the
fastmap command for an experiment and then extended the basic algorithm
and added the extension part in Feburary 2013 to make BWA-MEM a fully
featured mapper.
bwa-0.7.9-r783 19 May 2014 bwa(1)
