odseq: Outlier detection in a multiple sequence alignment
In odseq: Outlier detection in multiple sequence alignments
Description
Usage
Arguments
Value
Author(s)
References
See Also
Examples
Description
This function will first compute a distance metric among every sequence in the multiple alignment. Then it will bootstrap an average score of these distance to provide information on the distribution of scores, which is used to distinguish outlier sequences with a certain threshold
Usage
1
odseq(msa_object, distance_metric = "linear", B = 100, threshold = 0.025)
Arguments
msa_object
An object of formal class MsaAAMultipleAlignment, as provided by the msa package.
distance_metric
A string indicating the type of distance metric to be computed. Either 'linear' and 'affine' is supported at the moment.
B
Integer indicating the number of bootstrap replicates to be run. The higher the more robust the detection should be.
threshold
Float indicating the probability to be left at the right of the bootstrap scores distribution when computing outliers. This parameter may need some tuning depending on each specific problem
Value
Returns a logical vector, where TRUE indicates an outlier.
Author(s)
Jos<c3><a9> Jim<c3><a9>nez <jose@jimenezluna.com>
References
[1] OD-seq: outlier detection in multiple sequence alignments. Peter Jehl, Fabian Sievers and Desmond G. Higgins. BMC Bioinformatics. 2015.
See Also
Examples
1
2
3
4
Example output
Loading required package: Biostrings
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
use default substitution matrix
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odseq documentation built on Nov. 8, 2020, 6:50 p.m.
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Description Usage Arguments Value Author(s) References See Also Examples
Description
This function will first compute a distance metric among every sequence in the multiple alignment. Then it will bootstrap an average score of these distance to provide information on the distribution of scores, which is used to distinguish outlier sequences with a certain threshold
Usage
1 | odseq(msa_object, distance_metric = "linear", B = 100, threshold = 0.025)
|
Arguments
msa_object |
An object of formal class |
distance_metric |
A string indicating the type of distance metric to be computed. Either |
B |
Integer indicating the number of bootstrap replicates to be run. The higher the more robust the detection should be. |
threshold |
Float indicating the probability to be left at the right of the bootstrap scores distribution when computing outliers. This parameter may need some tuning depending on each specific problem |
Value
Returns a logical vector, where TRUE indicates an outlier.
Author(s)
Jos<c3><a9> Jim<c3><a9>nez <jose@jimenezluna.com>
References
[1] OD-seq: outlier detection in multiple sequence alignments. Peter Jehl, Fabian Sievers and Desmond G. Higgins. BMC Bioinformatics. 2015.
See Also
Examples
1 2 3 4 |
Example output
Loading required package: Biostrings
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
use default substitution matrix
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FALSE
D4I4P5.13.88
FALSE
E5BB17.42.117
FALSE
A0A0C8ZVD0.1.76
FALSE
A0A0F7JHC1.1.76
FALSE
B0ZE05.1.76
FALSE
B1MUC0.1.76
FALSE
M7RET1.1.76
FALSE
M8QJN2.1.76
FALSE
Q9KJ82.1.76
FALSE
S4KUZ8.1.76
FALSE
T2QBL4.1.76
FALSE
B0EYM2.1.76
FALSE
E9YM65.1.76
FALSE
K3K332.1.76
FALSE
A0A060RIR1.1.76
FALSE
A9LK87.1.76
FALSE
D8B5E1.1.76
FALSE
G3CAG9.1.76
FALSE
G3CAS3.1.76
FALSE
D0QML3.1.76
FALSE
G3CA69.1.76
FALSE
B4TLV4.1.76
FALSE
F0JY99.1.76
FALSE
H3RLY1.1.76
FALSE
Y1GKL8.1.76
FALSE
J5UN29.1.64
FALSE
A0A0A3ZSY6.1.77
FALSE
E5YNK1.1.74
FALSE
Q70W75.1.74
FALSE
A0A0F5PHW8.1.74
FALSE
A0A0E4G3K9.1.74
FALSE
C4K638.1.74
FALSE
A0A068Z196.1.75
FALSE
U2L622.1.77
FALSE
E6WMF1.1.77
FALSE
A0A0F6VXC8.10.79
FALSE
V5U7C5.1.63
FALSE
C9Y5R7.8.79
FALSE
R4IT59.8.78
FALSE
A0A0F8GEA6.1.78
FALSE
A0A085HRR6.9.59
FALSE
B2CBF1.1.79
FALSE
A0A0E2Q9I2.1.75
FALSE
A0A0E2QEH4.17.62
FALSE
W8UA11.1.72
FALSE
B7UF62.1.74
FALSE
K9W7U5.16.49
FALSE
D8G1Y5.17.50
FALSE
A0A0D8ZNJ1.15.48
FALSE
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FALSE
Q8YJV9.4.49
FALSE
A0A0D6K9Y8.15.50
FALSE
L7L2A9.46.83
FALSE
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FALSE
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FALSE
E3DL53.2.68
FALSE
Q7X3U6.1.66
FALSE
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FALSE
Q8GEG7.1.66
FALSE
H8NZG5.2.67
FALSE
H2J1I3.2.67
FALSE
A0A085G0L2.2.67
FALSE
A0A085NVQ6.3.66
FALSE
D8ARD1.3.66
FALSE
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FALSE
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FALSE
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FALSE
T9A0E0.3.66
FALSE
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FALSE
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FALSE
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FALSE
A0A0C2WIL6.36.77
FALSE
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FALSE
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FALSE
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FALSE
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FALSE
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FALSE
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FALSE
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