PairwiseAlignments-io: Write a PairwiseAlignments object to a file
In Biostrings: Efficient manipulation of biological strings
Description
Usage
Arguments
Details
Note
Author(s)
References
See Also
Examples
Description
The writePairwiseAlignments function writes a
PairwiseAlignments object to a file.
Only the "pair" format is supported at the moment.
Usage
1
writePairwiseAlignments(x, file="", Matrix=NA, block.width=50)
Arguments
x
A PairwiseAlignments object, typically returned by the
pairwiseAlignment function.
file
A connection, or a character string naming the file to print
to. If "" (the default), writePairwiseAlignments
prints to the standard output connection (aka the console)
unless redirected by sink.
If it is "|cmd", the output is piped to the command given
by cmd, by opening a pipe connection.
Matrix
A single string containing the name of the substitution matrix
(e.g. "BLOSUM50") used for the alignment.
See the substitutionMatrix argument of the
pairwiseAlignment function for the details.
See ?substitution.matrices for a list of
predefined substitution matrices available in the Biostrings package.
block.width
A single integer specifying the maximum number of sequence
letters (including the "-" letter, which represents gaps)
per line.
Details
The "pair" format is one of the numerous pairwise sequence alignment
formats supported by the EMBOSS software. See
http://emboss.sourceforge.net/docs/themes/AlignFormats.html
for a brief (and rather informal) description of this format.
Note
This brief description of the "pair" format suggests that
it is best suited for global pairwise alignments,
because, in that case, the original pattern and subject sequences
can be inferred (by just removing the gaps).
However, even though the "pair" format can also be used for non global
pairwise alignments (i.e. for global-local, local-global,
and local pairwise alignments), in that case the original
pattern and subject sequences cannot be inferred. This is because
the alignment written to the file doesn't necessarily span the entire
pattern (if type(x) is local-global or local)
or the entire subject (if type(x) is global-local
or local).
As a consequence, the writePairwiseAlignments function can be
used on a PairwiseAlignments object x containing non global
alignments (i.e. with type(x) != "global"), but with the 2 following
caveats:
The type of the alignments (type(x)) is not written
to the file.
The original pattern and subject sequences cannot be inferred.
Furthermore, there is no way to infer their lengths (because
we don't know whether they were trimmed or not).
Also note that the pairwiseAlignment function
interprets the gapOpening and gapExtension arguments
differently than most other alignment tools. As a consequence
the values of the Gap_penalty and Extend_penalty fields written to
the file are not the same as the values that were passed to the
gapOpening and gapExtension arguments. With the
following relationship:
Gap_penalty = gapOpening + gapExtension
Extend_penalty = gapExtension
Author(s)
H. Pag<c3><a8>s
References
http://emboss.sourceforge.net/docs/themes/AlignFormats.html
See Also
-
pairwiseAlignment
-
PairwiseAlignments-class
-
substitution.matrices
Examples
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## ---------------------------------------------------------------------
## A. WITH ONE PAIR
## ---------------------------------------------------------------------
pattern <- DNAString("CGTACGTAACGTTCGT")
subject <- DNAString("CGTCGTCGTCCGTAA")
pa1 <- pairwiseAlignment(pattern, subject)
pa1
writePairwiseAlignments(pa1)
writePairwiseAlignments(pa1, block.width=10)
## The 2 bottom-right numbers (16 and 15) are the lengths of
## the original pattern and subject, respectively.
pa2 <- pairwiseAlignment(pattern, subject, type="global-local")
pa2 # score is different!
writePairwiseAlignments(pa2)
## By just looking at the file, we can't tell the length of the
## original subject! Could be 13, could be more...
pattern <- DNAString("TCAACTTAACTT")
subject <- DNAString("GGGCAACAACGGG")
pa3 <- pairwiseAlignment(pattern, subject, type="global-local",
gapOpening=-2, gapExtension=-1)
writePairwiseAlignments(pa3)
## ---------------------------------------------------------------------
## B. WITH MORE THAN ONE PAIR (AND NAMED PATTERNS)
## ---------------------------------------------------------------------
pattern <- DNAStringSet(c(myp1="ACCA", myp2="ACGCA", myp3="ACGGCA"))
pa4 <- pairwiseAlignment(pattern, subject)
pa4
writePairwiseAlignments(pa4)
## ---------------------------------------------------------------------
## C. REPRODUCING THE ALIGNMENT SHOWN AT
## http://emboss.sourceforge.net/docs/themes/alnformats/align.pair
## ---------------------------------------------------------------------
pattern <- c("TSPASIRPPAGPSSRPAMVSSRRTRPSPPGPRRPTGRPCCSAAPRRPQAT",
"GGWKTCSGTCTTSTSTRHRGRSGWSARTTTAACLRASRKSMRAACSRSAG",
"SRPNRFAPTLMSSCITSTTGPPAWAGDRSHE")
subject <- c("TSPASIRPPAGPSSRRPSPPGPRRPTGRPCCSAAPRRPQATGGWKTCSGT",
"CTTSTSTRHRGRSGWRASRKSMRAACSRSAGSRPNRFAPTLMSSCITSTT",
"GPPAWAGDRSHE")
pattern <- unlist(AAStringSet(pattern))
subject <- unlist(AAStringSet(subject))
pattern # original pattern
subject # original subject
data(BLOSUM62)
pa5 <- pairwiseAlignment(pattern, subject,
substitutionMatrix=BLOSUM62,
gapOpening=9.5, gapExtension=0.5)
pa5
writePairwiseAlignments(pa5, Matrix="BLOSUM62")
Example output
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, sd, var, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, cbind, colMeans, colSums, colnames, do.call,
duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
lapply, lengths, mapply, match, mget, order, paste, pmax, pmax.int,
pmin, pmin.int, rank, rbind, rowMeans, rowSums, rownames, sapply,
setdiff, sort, table, tapply, union, unique, unsplit, which,
which.max, which.min
Loading required package: S4Vectors
Loading required package: stats4
Attaching package: 'S4Vectors'
The following object is masked from 'package:base':
expand.grid
Loading required package: IRanges
Loading required package: XVector
Attaching package: 'Biostrings'
The following object is masked from 'package:base':
strsplit
Global PairwiseAlignmentsSingleSubject (1 of 1)
pattern: [1] CGTACGTAACGTTCGT
subject: [1] CGT-CGT--CGTCCGT
score: -32.11822
########################################
# Program: Biostrings (version 2.44.2), a Bioconductor package
# Rundate: Fri Jan 12 18:58:29 2018
########################################
#=======================================
#
# Aligned_sequences: 2
# 1: P1
# 2: S1
# Matrix: NA
# Gap_penalty: 14.0
# Extend_penalty: 4.0
#
# Length: 18
# Identity: 12/18 (66.7%)
# Similarity: NA/18 (NA%)
# Gaps: 5/18 (27.8%)
# Score: -32.11822
#
#
#=======================================
P1 1 CGTACGTAACGTTCGT-- 16
||| ||| ||| |||
S1 1 CGT-CGT--CGTCCGTAA 15
#---------------------------------------
#---------------------------------------
########################################
# Program: Biostrings (version 2.44.2), a Bioconductor package
# Rundate: Fri Jan 12 18:58:29 2018
########################################
#=======================================
#
# Aligned_sequences: 2
# 1: P1
# 2: S1
# Matrix: NA
# Gap_penalty: 14.0
# Extend_penalty: 4.0
#
# Length: 18
# Identity: 12/18 (66.7%)
# Similarity: NA/18 (NA%)
# Gaps: 5/18 (27.8%)
# Score: -32.11822
#
#
#=======================================
P1 1 CGTACGTAAC 10
||| ||| |
S1 1 CGT-CGT--C 7
P1 11 GTTCGT-- 16
|| |||
S1 8 GTCCGTAA 15
#---------------------------------------
#---------------------------------------
Global-Local PairwiseAlignmentsSingleSubject (1 of 1)
pattern: [1] CGTACGTAACGTTCGT
subject: [1] CGT-CGT--CGTCCGT
score: -14.11821
########################################
# Program: Biostrings (version 2.44.2), a Bioconductor package
# Rundate: Fri Jan 12 18:58:30 2018
########################################
#=======================================
#
# Aligned_sequences: 2
# 1: P1
# 2: S1
# Matrix: NA
# Gap_penalty: 14.0
# Extend_penalty: 4.0
#
# Length: 16
# Identity: 12/16 (75.0%)
# Similarity: NA/16 (NA%)
# Gaps: 3/16 (18.8%)
# Score: -14.11821
#
#
#=======================================
P1 1 CGTACGTAACGTTCGT 16
||| ||| ||| |||
S1 1 CGT-CGT--CGTCCGT 13
#---------------------------------------
#---------------------------------------
########################################
# Program: Biostrings (version 2.44.2), a Bioconductor package
# Rundate: Fri Jan 12 18:58:30 2018
########################################
#=======================================
#
# Aligned_sequences: 2
# 1: P1
# 2: S1
# Matrix: NA
# Gap_penalty: 3.0
# Extend_penalty: 1.0
#
# Length: 12
# Identity: 7/12 (58.3%)
# Similarity: NA/12 (NA%)
# Gaps: 5/12 (41.7%)
# Score: 2.872293
#
#
#=======================================
P1 1 TCAACTTAACTT 12
|||| |||
S1 4 -CAAC--AAC-- 10
#---------------------------------------
#---------------------------------------
Global PairwiseAlignmentsSingleSubject (1 of 3)
pattern: [1] ACCA
subject: [5] AACA
score: -55.95402
########################################
# Program: Biostrings (version 2.44.2), a Bioconductor package
# Rundate: Fri Jan 12 18:58:31 2018
########################################
#=======================================
#
# Aligned_sequences: 2
# 1: myp1
# 2: S1
# Matrix: NA
# Gap_penalty: 14.0
# Extend_penalty: 4.0
#
# Length: 13
# Identity: 3/13 (23.1%)
# Similarity: NA/13 (NA%)
# Gaps: 9/13 (69.2%)
# Score: -55.95402
#
#
#=======================================
myp1 1 ----ACCA----- 4
| ||
S1 1 GGGCAACAACGGG 13
#=======================================
#
# Aligned_sequences: 2
# 1: myp2
# 2: S1
# Matrix: NA
# Gap_penalty: 14.0
# Extend_penalty: 4.0
#
# Length: 13
# Identity: 3/13 (23.1%)
# Similarity: NA/13 (NA%)
# Gaps: 8/13 (61.5%)
# Score: -47.8533
#
#
#=======================================
myp2 1 --------ACGCA 5
|||
S1 1 GGGCAACAACGGG 13
#=======================================
#
# Aligned_sequences: 2
# 1: myp3
# 2: S1
# Matrix: NA
# Gap_penalty: 14.0
# Extend_penalty: 4.0
#
# Length: 14
# Identity: 4/14 (28.6%)
# Similarity: NA/14 (NA%)
# Gaps: 9/14 (64.3%)
# Score: -53.97226
#
#
#=======================================
myp3 1 --------ACGGCA 6
||||
S1 1 GGGCAACAACGGG- 13
#---------------------------------------
#---------------------------------------
131-letter "AAString" instance
seq: TSPASIRPPAGPSSRPAMVSSRRTRPSPPGPRRPTG...SRSAGSRPNRFAPTLMSSCITSTTGPPAWAGDRSHE
112-letter "AAString" instance
seq: TSPASIRPPAGPSSRRPSPPGPRRPTGRPCCSAAPR...SRSAGSRPNRFAPTLMSSCITSTTGPPAWAGDRSHE
Global PairwiseAlignmentsSingleSubject (1 of 1)
pattern: [1] TSPASIRPPAGPSSRPAMVSSRRTRPSPPGPRRPT...SAGSRPNRFAPTLMSSCITSTTGPPAWAGDRSHE
subject: [1] TSPASIRPPAGPSSR---------RPSPPGPRRPT...SAGSRPNRFAPTLMSSCITSTTGPPAWAGDRSHE
score: 591.5
########################################
# Program: Biostrings (version 2.44.2), a Bioconductor package
# Rundate: Fri Jan 12 18:58:31 2018
########################################
#=======================================
#
# Aligned_sequences: 2
# 1: P1
# 2: S1
# Matrix: BLOSUM62
# Gap_penalty: 10.0
# Extend_penalty: 0.5
#
# Length: 131
# Identity: 112/131 (85.5%)
# Similarity: NA/131 (NA%)
# Gaps: 19/131 (14.5%)
# Score: 591.5
#
#
#=======================================
P1 1 TSPASIRPPAGPSSRPAMVSSRRTRPSPPGPRRPTGRPCCSAAPRRPQAT 50
||||||||||||||| ||||||||||||||||||||||||||
S1 1 TSPASIRPPAGPSSR---------RPSPPGPRRPTGRPCCSAAPRRPQAT 41
P1 51 GGWKTCSGTCTTSTSTRHRGRSGWSARTTTAACLRASRKSMRAACSRSAG 100
|||||||||||||||||||||||| ||||||||||||||||
S1 42 GGWKTCSGTCTTSTSTRHRGRSGW----------RASRKSMRAACSRSAG 81
P1 101 SRPNRFAPTLMSSCITSTTGPPAWAGDRSHE 131
|||||||||||||||||||||||||||||||
S1 82 SRPNRFAPTLMSSCITSTTGPPAWAGDRSHE 112
#---------------------------------------
#---------------------------------------
Biostrings documentation built on Nov. 8, 2020, 11:12 p.m.
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Description Usage Arguments Details Note Author(s) References See Also Examples
Description
The writePairwiseAlignments function writes a
PairwiseAlignments object to a file.
Only the "pair" format is supported at the moment.
Usage
1 | writePairwiseAlignments(x, file="", Matrix=NA, block.width=50)
|
Arguments
x |
A PairwiseAlignments object, typically returned by the
|
file |
A connection, or a character string naming the file to print
to. If |
Matrix |
A single string containing the name of the substitution matrix
(e.g. |
block.width |
A single integer specifying the maximum number of sequence letters (including the "-" letter, which represents gaps) per line. |
Details
The "pair" format is one of the numerous pairwise sequence alignment formats supported by the EMBOSS software. See http://emboss.sourceforge.net/docs/themes/AlignFormats.html for a brief (and rather informal) description of this format.
Note
This brief description of the "pair" format suggests that it is best suited for global pairwise alignments, because, in that case, the original pattern and subject sequences can be inferred (by just removing the gaps).
However, even though the "pair" format can also be used for non global
pairwise alignments (i.e. for global-local, local-global,
and local pairwise alignments), in that case the original
pattern and subject sequences cannot be inferred. This is because
the alignment written to the file doesn't necessarily span the entire
pattern (if type(x) is local-global or local)
or the entire subject (if type(x) is global-local
or local).
As a consequence, the writePairwiseAlignments function can be
used on a PairwiseAlignments object x containing non global
alignments (i.e. with type(x) != "global"), but with the 2 following
caveats:
The type of the alignments (
type(x)) is not written to the file.The original pattern and subject sequences cannot be inferred. Furthermore, there is no way to infer their lengths (because we don't know whether they were trimmed or not).
Also note that the pairwiseAlignment function
interprets the gapOpening and gapExtension arguments
differently than most other alignment tools. As a consequence
the values of the Gap_penalty and Extend_penalty fields written to
the file are not the same as the values that were passed to the
gapOpening and gapExtension arguments. With the
following relationship:
Gap_penalty = gapOpening + gapExtension
Extend_penalty = gapExtension
Author(s)
H. Pag<c3><a8>s
References
http://emboss.sourceforge.net/docs/themes/AlignFormats.html
See Also
-
pairwiseAlignment -
PairwiseAlignments-class
-
substitution.matrices
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 | ## ---------------------------------------------------------------------
## A. WITH ONE PAIR
## ---------------------------------------------------------------------
pattern <- DNAString("CGTACGTAACGTTCGT")
subject <- DNAString("CGTCGTCGTCCGTAA")
pa1 <- pairwiseAlignment(pattern, subject)
pa1
writePairwiseAlignments(pa1)
writePairwiseAlignments(pa1, block.width=10)
## The 2 bottom-right numbers (16 and 15) are the lengths of
## the original pattern and subject, respectively.
pa2 <- pairwiseAlignment(pattern, subject, type="global-local")
pa2 # score is different!
writePairwiseAlignments(pa2)
## By just looking at the file, we can't tell the length of the
## original subject! Could be 13, could be more...
pattern <- DNAString("TCAACTTAACTT")
subject <- DNAString("GGGCAACAACGGG")
pa3 <- pairwiseAlignment(pattern, subject, type="global-local",
gapOpening=-2, gapExtension=-1)
writePairwiseAlignments(pa3)
## ---------------------------------------------------------------------
## B. WITH MORE THAN ONE PAIR (AND NAMED PATTERNS)
## ---------------------------------------------------------------------
pattern <- DNAStringSet(c(myp1="ACCA", myp2="ACGCA", myp3="ACGGCA"))
pa4 <- pairwiseAlignment(pattern, subject)
pa4
writePairwiseAlignments(pa4)
## ---------------------------------------------------------------------
## C. REPRODUCING THE ALIGNMENT SHOWN AT
## http://emboss.sourceforge.net/docs/themes/alnformats/align.pair
## ---------------------------------------------------------------------
pattern <- c("TSPASIRPPAGPSSRPAMVSSRRTRPSPPGPRRPTGRPCCSAAPRRPQAT",
"GGWKTCSGTCTTSTSTRHRGRSGWSARTTTAACLRASRKSMRAACSRSAG",
"SRPNRFAPTLMSSCITSTTGPPAWAGDRSHE")
subject <- c("TSPASIRPPAGPSSRRPSPPGPRRPTGRPCCSAAPRRPQATGGWKTCSGT",
"CTTSTSTRHRGRSGWRASRKSMRAACSRSAGSRPNRFAPTLMSSCITSTT",
"GPPAWAGDRSHE")
pattern <- unlist(AAStringSet(pattern))
subject <- unlist(AAStringSet(subject))
pattern # original pattern
subject # original subject
data(BLOSUM62)
pa5 <- pairwiseAlignment(pattern, subject,
substitutionMatrix=BLOSUM62,
gapOpening=9.5, gapExtension=0.5)
pa5
writePairwiseAlignments(pa5, Matrix="BLOSUM62")
|
Example output
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, sd, var, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, cbind, colMeans, colSums, colnames, do.call,
duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
lapply, lengths, mapply, match, mget, order, paste, pmax, pmax.int,
pmin, pmin.int, rank, rbind, rowMeans, rowSums, rownames, sapply,
setdiff, sort, table, tapply, union, unique, unsplit, which,
which.max, which.min
Loading required package: S4Vectors
Loading required package: stats4
Attaching package: 'S4Vectors'
The following object is masked from 'package:base':
expand.grid
Loading required package: IRanges
Loading required package: XVector
Attaching package: 'Biostrings'
The following object is masked from 'package:base':
strsplit
Global PairwiseAlignmentsSingleSubject (1 of 1)
pattern: [1] CGTACGTAACGTTCGT
subject: [1] CGT-CGT--CGTCCGT
score: -32.11822
########################################
# Program: Biostrings (version 2.44.2), a Bioconductor package
# Rundate: Fri Jan 12 18:58:29 2018
########################################
#=======================================
#
# Aligned_sequences: 2
# 1: P1
# 2: S1
# Matrix: NA
# Gap_penalty: 14.0
# Extend_penalty: 4.0
#
# Length: 18
# Identity: 12/18 (66.7%)
# Similarity: NA/18 (NA%)
# Gaps: 5/18 (27.8%)
# Score: -32.11822
#
#
#=======================================
P1 1 CGTACGTAACGTTCGT-- 16
||| ||| ||| |||
S1 1 CGT-CGT--CGTCCGTAA 15
#---------------------------------------
#---------------------------------------
########################################
# Program: Biostrings (version 2.44.2), a Bioconductor package
# Rundate: Fri Jan 12 18:58:29 2018
########################################
#=======================================
#
# Aligned_sequences: 2
# 1: P1
# 2: S1
# Matrix: NA
# Gap_penalty: 14.0
# Extend_penalty: 4.0
#
# Length: 18
# Identity: 12/18 (66.7%)
# Similarity: NA/18 (NA%)
# Gaps: 5/18 (27.8%)
# Score: -32.11822
#
#
#=======================================
P1 1 CGTACGTAAC 10
||| ||| |
S1 1 CGT-CGT--C 7
P1 11 GTTCGT-- 16
|| |||
S1 8 GTCCGTAA 15
#---------------------------------------
#---------------------------------------
Global-Local PairwiseAlignmentsSingleSubject (1 of 1)
pattern: [1] CGTACGTAACGTTCGT
subject: [1] CGT-CGT--CGTCCGT
score: -14.11821
########################################
# Program: Biostrings (version 2.44.2), a Bioconductor package
# Rundate: Fri Jan 12 18:58:30 2018
########################################
#=======================================
#
# Aligned_sequences: 2
# 1: P1
# 2: S1
# Matrix: NA
# Gap_penalty: 14.0
# Extend_penalty: 4.0
#
# Length: 16
# Identity: 12/16 (75.0%)
# Similarity: NA/16 (NA%)
# Gaps: 3/16 (18.8%)
# Score: -14.11821
#
#
#=======================================
P1 1 CGTACGTAACGTTCGT 16
||| ||| ||| |||
S1 1 CGT-CGT--CGTCCGT 13
#---------------------------------------
#---------------------------------------
########################################
# Program: Biostrings (version 2.44.2), a Bioconductor package
# Rundate: Fri Jan 12 18:58:30 2018
########################################
#=======================================
#
# Aligned_sequences: 2
# 1: P1
# 2: S1
# Matrix: NA
# Gap_penalty: 3.0
# Extend_penalty: 1.0
#
# Length: 12
# Identity: 7/12 (58.3%)
# Similarity: NA/12 (NA%)
# Gaps: 5/12 (41.7%)
# Score: 2.872293
#
#
#=======================================
P1 1 TCAACTTAACTT 12
|||| |||
S1 4 -CAAC--AAC-- 10
#---------------------------------------
#---------------------------------------
Global PairwiseAlignmentsSingleSubject (1 of 3)
pattern: [1] ACCA
subject: [5] AACA
score: -55.95402
########################################
# Program: Biostrings (version 2.44.2), a Bioconductor package
# Rundate: Fri Jan 12 18:58:31 2018
########################################
#=======================================
#
# Aligned_sequences: 2
# 1: myp1
# 2: S1
# Matrix: NA
# Gap_penalty: 14.0
# Extend_penalty: 4.0
#
# Length: 13
# Identity: 3/13 (23.1%)
# Similarity: NA/13 (NA%)
# Gaps: 9/13 (69.2%)
# Score: -55.95402
#
#
#=======================================
myp1 1 ----ACCA----- 4
| ||
S1 1 GGGCAACAACGGG 13
#=======================================
#
# Aligned_sequences: 2
# 1: myp2
# 2: S1
# Matrix: NA
# Gap_penalty: 14.0
# Extend_penalty: 4.0
#
# Length: 13
# Identity: 3/13 (23.1%)
# Similarity: NA/13 (NA%)
# Gaps: 8/13 (61.5%)
# Score: -47.8533
#
#
#=======================================
myp2 1 --------ACGCA 5
|||
S1 1 GGGCAACAACGGG 13
#=======================================
#
# Aligned_sequences: 2
# 1: myp3
# 2: S1
# Matrix: NA
# Gap_penalty: 14.0
# Extend_penalty: 4.0
#
# Length: 14
# Identity: 4/14 (28.6%)
# Similarity: NA/14 (NA%)
# Gaps: 9/14 (64.3%)
# Score: -53.97226
#
#
#=======================================
myp3 1 --------ACGGCA 6
||||
S1 1 GGGCAACAACGGG- 13
#---------------------------------------
#---------------------------------------
131-letter "AAString" instance
seq: TSPASIRPPAGPSSRPAMVSSRRTRPSPPGPRRPTG...SRSAGSRPNRFAPTLMSSCITSTTGPPAWAGDRSHE
112-letter "AAString" instance
seq: TSPASIRPPAGPSSRRPSPPGPRRPTGRPCCSAAPR...SRSAGSRPNRFAPTLMSSCITSTTGPPAWAGDRSHE
Global PairwiseAlignmentsSingleSubject (1 of 1)
pattern: [1] TSPASIRPPAGPSSRPAMVSSRRTRPSPPGPRRPT...SAGSRPNRFAPTLMSSCITSTTGPPAWAGDRSHE
subject: [1] TSPASIRPPAGPSSR---------RPSPPGPRRPT...SAGSRPNRFAPTLMSSCITSTTGPPAWAGDRSHE
score: 591.5
########################################
# Program: Biostrings (version 2.44.2), a Bioconductor package
# Rundate: Fri Jan 12 18:58:31 2018
########################################
#=======================================
#
# Aligned_sequences: 2
# 1: P1
# 2: S1
# Matrix: BLOSUM62
# Gap_penalty: 10.0
# Extend_penalty: 0.5
#
# Length: 131
# Identity: 112/131 (85.5%)
# Similarity: NA/131 (NA%)
# Gaps: 19/131 (14.5%)
# Score: 591.5
#
#
#=======================================
P1 1 TSPASIRPPAGPSSRPAMVSSRRTRPSPPGPRRPTGRPCCSAAPRRPQAT 50
||||||||||||||| ||||||||||||||||||||||||||
S1 1 TSPASIRPPAGPSSR---------RPSPPGPRRPTGRPCCSAAPRRPQAT 41
P1 51 GGWKTCSGTCTTSTSTRHRGRSGWSARTTTAACLRASRKSMRAACSRSAG 100
|||||||||||||||||||||||| ||||||||||||||||
S1 42 GGWKTCSGTCTTSTSTRHRGRSGW----------RASRKSMRAACSRSAG 81
P1 101 SRPNRFAPTLMSSCITSTTGPPAWAGDRSHE 131
|||||||||||||||||||||||||||||||
S1 82 SRPNRFAPTLMSSCITSTTGPPAWAGDRSHE 112
#---------------------------------------
#---------------------------------------
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