Biostrings包测试2_MultipleAlignment Objects _20200130Thursday
1.设置当前工作目录
getwd()
setwd("./Biostrings/")
2.导入R包
library(Biostrings)
3.测试：MultipleAlignment Objects
3.1 Introduction
#@ The DNAMultipleAlignment RNAMultipleAlignment and AAMultipleAlignment classes allow users to represent groups of aligned DNA, RNA or amino acid sequences as a single object. The frame of reference for aligned sequences is static, so manipulation of these objects is confined to be non-destructive. In practice, this means that these objects contain slots to mask ranges of rows and columns on the original sequence.
#@ These masks are then respected by methods that manipulate and display the objects, allowing the user to remove or expose columns and rows without invalidating the original alignment.
3.2 Creation and masking
To create a MultipleAlignment, call the appropriate read function to read in and parse the original alignment.
There are functions to read clustaW, Phylip and Stolkholm data formats.
origMAlign <- readDNAMultipleAlignment(filepath = system.file(“extdata”, “msx2_mRNA.aln”, package=“Biostrings”), format=“clustal”)
phylipMAlign <- readAAMultipleAlignment(filepath = system.file(“extdata”, “Phylip.txt”, package = “Biostrings”), format= “phylip”)
#@ Rows can be renamed with rownames.
rownames(origMAlign)
[1] “gi|84452153|ref|NM_002449.4|”
[2] “gi|208431713|ref|NM_001135625.”
[3] “gi|118601823|ref|NM_001079614.”
[4] “gi|114326503|ref|NM_013601.2|”
[5] “gi|119220589|ref|NM_012982.3|”
[6] “gi|148540149|ref|NM_001003098.”
[7] “gi|45383056|ref|NM_204559.1|”
[8] “gi|213515133|ref|NM_001141603.”
rownames(origMAlign) <- c(“Human”,“Chimp”,“Cow”,“Mouse”,“Rat”, “Dog”,“Chicken”,“Salmon”)
origMAlign
DNAMultipleAlignment with 8 rows and 2343 columns
aln names
[1] -----TCCCGTCTCCGCAGCAAAAAAGTTTGAGTCGCCGCTGCCGGGTTGC…TTATTGCAGTAAAGTTTGTCCAAACTCACAATTAAAAAAAAAAAAAAAAA Human
[2] ---------------------------------------------------…-------------------------------------------------- Chimp
[3] ---------------------------------------------------…-------------------------------------------------- Cow
[4] ----------------------AAAAGTTGGAGTCTTCGCTTGAGAGTTGC…TTATTGCAGT---------------------------------------- Mouse
[5] ---------------------------------------------------…TTATTGCAGTAAA------------------------------------- Rat
[6] ---------------------------------------------------…-------------------------------------------------- Dog
[7] --------------CGGCTCCGCAGCGCCTCACTCGCGCAGTCCCCGCGCA…-------------------------------------------------- Chicken
[8] GGGGGAGACTTCAGAAGTTGTTGTCCTCTCCGCTGATAACAGTTGAGATGC…-------------------------------------------------- Salmon
#@ To see a more detailed version of your MultipleAlignment object, you can use the detail method, which will show the details of the alignment interleaved and without the rows and columns that you have masked out.
detail(origMAlign)
#@ Applying masks is a simple matter of specifying which ranges to hide.
maskTest <- origMAlign
maskTest
DNAMultipleAlignment with 8 rows and 2343 columns
aln names
[1] ###################################################…################################################## Human
[2] ###################################################…################################################## Chimp
[3] ###################################################…################################################## Cow
[4] ----------------------AAAAGTTGGAGTCTTCGCTTGAGAGTTGC…TTATTGCAGT---------------------------------------- Mouse
[5] ---------------------------------------------------…TTATTGCAGTAAA------------------------------------- Rat
[6] ---------------------------------------------------…-------------------------------------------------- Dog
[7] --------------CGGCTCCGCAGCGCCTCACTCGCGCAGTCCCCGCGCA…-------------------------------------------------- Chicken
[8] GGGGGAGACTTCAGAAGTTGTTGTCCTCTCCGCTGATAACAGTTGAGATGC…-------------------------------------------------- Salmon
rowmask(maskTest) <- IRanges(start=1,end=3)
rowmask(maskTest)
NormalIRanges object with 1 range and 0 metadata columns:
start end width
[1] 1 3 3
maskTest
DNAMultipleAlignment with 8 rows and 2343 columns
aln names
[1] ###################################################…################################################## Human
[2] ###################################################…################################################## Chimp
[3] ###################################################…################################################## Cow
[4] ----------------------AAAAGTTGGAGTCTTCGCTTGAGAGTTGC…TTATTGCAGT---------------------------------------- Mouse
[5] ---------------------------------------------------…TTATTGCAGTAAA------------------------------------- Rat
[6] ---------------------------------------------------…-------------------------------------------------- Dog
[7] --------------CGGCTCCGCAGCGCCTCACTCGCGCAGTCCCCGCGCA…-------------------------------------------------- Chicken
[8] GGGGGAGACTTCAGAAGTTGTTGTCCTCTCCGCTGATAACAGTTGAGATGC…-------------------------------------------------- Salmon
colmask(maskTest) <- IRanges(start=c(1,1000),end=c(500,2343))
colmask(maskTest)
NormalIRanges object with 2 ranges and 0 metadata columns:
start end width
[1] 1 500 500
[2] 1000 2343 1344
maskTest
DNAMultipleAlignment with 8 rows and 2343 columns
aln names
[1] ###################################################…################################################## Human
[2] ###################################################…################################################## Chimp
[3] ###################################################…################################################## Cow
[4] ###################################################…################################################## Mouse
[5] ###################################################…################################################## Rat
[6] ###################################################…################################################## Dog
[7] ###################################################…################################################## Chicken
[8] ###################################################…################################################## Salmon
#@ Remove row and column masks by assigning NULL:
rowmask(maskTest) <- NULL
rowmask(maskTest)
NormalIRanges object with 0 ranges and 0 metadata columns:
start end width
colmask(maskTest) <- NULL
colmask(maskTest)
NormalIRanges object with 0 ranges and 0 metadata columns:
start end width
maskTest
DNAMultipleAlignment with 8 rows and 2343 columns
aln names
[1] -----TCCCGTCTCCGCAGCAAAAAAGTTTGAGTCGCCGCTGCCGGGTTGC…TTATTGCAGTAAAGTTTGTCCAAACTCACAATTAAAAAAAAAAAAAAAAA Human
[2] ---------------------------------------------------…-------------------------------------------------- Chimp
[3] ---------------------------------------------------…-------------------------------------------------- Cow
[4] ----------------------AAAAGTTGGAGTCTTCGCTTGAGAGTTGC…TTATTGCAGT---------------------------------------- Mouse
[5] ---------------------------------------------------…TTATTGCAGTAAA------------------------------------- Rat
[6] ---------------------------------------------------…-------------------------------------------------- Dog
[7] --------------CGGCTCCGCAGCGCCTCACTCGCGCAGTCCCCGCGCA…-------------------------------------------------- Chicken
[8] GGGGGAGACTTCAGAAGTTGTTGTCCTCTCCGCTGATAACAGTTGAGATGC…-------------------------------------------------- Salmon
#@ When setting a mask, you might want to specify the rows or columns to keep, rather than to hide. To do that, use the invert argument. Taking the above example, we can set the exact same masks as before by specifying their inverse and using invert=TRUE.
rowmask(maskTest, invert=TRUE) <- IRanges(start=4,end=8)
rowmask(maskTest)
NormalIRanges object with 1 range and 0 metadata columns:
start end width
[1] 1 3 3
maskTest
DNAMultipleAlignment with 8 rows and 2343 columns
aln names
[1] ###################################################…################################################## Human
[2] ###################################################…################################################## Chimp
[3] ###################################################…################################################## Cow
[4] ----------------------AAAAGTTGGAGTCTTCGCTTGAGAGTTGC…TTATTGCAGT---------------------------------------- Mouse
[5] ---------------------------------------------------…TTATTGCAGTAAA------------------------------------- Rat
[6] ---------------------------------------------------…-------------------------------------------------- Dog
[7] --------------CGGCTCCGCAGCGCCTCACTCGCGCAGTCCCCGCGCA…-------------------------------------------------- Chicken
[8] GGGGGAGACTTCAGAAGTTGTTGTCCTCTCCGCTGATAACAGTTGAGATGC…-------------------------------------------------- Salmon
colmask(maskTest, invert=TRUE) <- IRanges(start=501,end=999)
colmask(maskTest)
NormalIRanges object with 2 ranges and 0 metadata columns:
start end width
[1] 1 500 500
[2] 1000 2343 1344
maskTest
DNAMultipleAlignment with 8 rows and 2343 columns
aln names
[1] ###################################################…################################################## Human
[2] ###################################################…################################################## Chimp
[3] ###################################################…################################################## Cow
[4] ###################################################…################################################## Mouse
[5] ###################################################…################################################## Rat
[6] ###################################################…################################################## Dog
[7] ###################################################…################################################## Chicken
[8] ###################################################…################################################## Salmon
In addition to being able to invert these masks, you can also choose the way in which the ranges you
provide will be merged with any existing masks. The append argument allows you to specify the way in
which new mask ranges will interact with any existing masks. By default, these masks will be the “union”
of the new mask and any existing masks, but you can also specify that these masks be the mask that results
from when you “intersect” the current mask and the new mask, or that the new mask simply “replace” the
current mask. The append argument can be used in combination with the invert argument to make things
even more interesting. In this case, the inversion of the mask will happen before it is combined with the
existing mask. For simplicity, I will only demonstrate this on rowmask, but it also works for colmask. Before
we begin, lets set the masks back to being NULL again.
#@ 1st lets null out the masks so we can have a fresh start.
colmask(maskTest) <- NULL
rowmask(maskTest) <- NULL
#@ Then we can do a series of examples, starting with the default which uses the “union” value for the append argument.
##@ Then we can demonstrate how the append argument works
rowmask(maskTest) <- IRanges(start=1,end=3)
maskTest
DNAMultipleAlignment with 8 rows and 2343 columns
aln names
[1] ###################################################…################################################## Human
[2] ###################################################…################################################## Chimp
[3] ###################################################…################################################## Cow
[4] ----------------------AAAAGTTGGAGTCTTCGCTTGAGAGTTGC…TTATTGCAGT---------------------------------------- Mouse
[5] ---------------------------------------------------…TTATTGCAGTAAA------------------------------------- Rat
[6] ---------------------------------------------------…-------------------------------------------------- Dog
[7] --------------CGGCTCCGCAGCGCCTCACTCGCGCAGTCCCCGCGCA…-------------------------------------------------- Chicken
[8] GGGGGAGACTTCAGAAGTTGTTGTCCTCTCCGCTGATAACAGTTGAGATGC…-------------------------------------------------- Salmon
rowmask(maskTest,append=“intersect”) <- IRanges(start=2,end=5)
maskTest
DNAMultipleAlignment with 8 rows and 2343 columns
aln names
[1] -----TCCCGTCTCCGCAGCAAAAAAGTTTGAGTCGCCGCTGCCGGGTTGC…TTATTGCAGTAAAGTTTGTCCAAACTCACAATTAAAAAAAAAAAAAAAAA Human
[2] ###################################################…################################################## Chimp
[3] ###################################################…################################################## Cow
[4] ----------------------AAAAGTTGGAGTCTTCGCTTGAGAGTTGC…TTATTGCAGT---------------------------------------- Mouse
[5] ---------------------------------------------------…TTATTGCAGTAAA------------------------------------- Rat
[6] ---------------------------------------------------…-------------------------------------------------- Dog
[7] --------------CGGCTCCGCAGCGCCTCACTCGCGCAGTCCCCGCGCA…-------------------------------------------------- Chicken
[8] GGGGGAGACTTCAGAAGTTGTTGTCCTCTCCGCTGATAACAGTTGAGATGC…-------------------------------------------------- Salmon
rowmask(maskTest,append=“replace”) <- IRanges(start=5,end=8)
maskTest
DNAMultipleAlignment with 8 rows and 2343 columns
aln names
[1] -----TCCCGTCTCCGCAGCAAAAAAGTTTGAGTCGCCGCTGCCGGGTTGC…TTATTGCAGTAAAGTTTGTCCAAACTCACAATTAAAAAAAAAAAAAAAAA Human
[2] ---------------------------------------------------…-------------------------------------------------- Chimp
[3] ---------------------------------------------------…-------------------------------------------------- Cow
[4] ----------------------AAAAGTTGGAGTCTTCGCTTGAGAGTTGC…TTATTGCAGT---------------------------------------- Mouse
[5] ###################################################…################################################## Rat
[6] ###################################################…################################################## Dog
[7] ###################################################…################################################## Chicken
[8] ###################################################…################################################## Salmon
rowmask(maskTest,append=“replace”,invert=TRUE) <- IRanges(start=5,end=8)
maskTest
DNAMultipleAlignment with 8 rows and 2343 columns
aln names
[1] ###################################################…################################################## Human
[2] ###################################################…################################################## Chimp
[3] ###################################################…################################################## Cow
[4] ###################################################…################################################## Mouse
[5] ---------------------------------------------------…TTATTGCAGTAAA------------------------------------- Rat
[6] ---------------------------------------------------…-------------------------------------------------- Dog
[7] --------------CGGCTCCGCAGCGCCTCACTCGCGCAGTCCCCGCGCA…-------------------------------------------------- Chicken
[8] GGGGGAGACTTCAGAAGTTGTTGTCCTCTCCGCTGATAACAGTTGAGATGC…-------------------------------------------------- Salmon
rowmask(maskTest,append=“union”) <- IRanges(start=7,end=8)
maskTest
DNAMultipleAlignment with 8 rows and 2343 columns
aln names
[1] ###################################################…################################################## Human
[2] ###################################################…################################################## Chimp
[3] ###################################################…################################################## Cow
[4] ###################################################…################################################## Mouse
[5] ---------------------------------------------------…TTATTGCAGTAAA------------------------------------- Rat
[6] ---------------------------------------------------…-------------------------------------------------- Dog
[7] ###################################################…################################################## Chicken
[8] ###################################################…################################################## Salmon
#@ The function maskMotif works on MultipleAlignment objects too, and takes the same arguments that it does elsewhere. maskMotif is useful for masking occurances of a string from columns where it is present in the consensus sequence.
tataMasked <- maskMotif(origMAlign, “TATA”)
colmask(tataMasked)
NormalIRanges object with 5 ranges and 0 metadata columns:
start end width
[1] 811 814 4
[2] 1180 1183 4
[3] 1186 1191 6
[4] 1204 1207 4
[5] 1218 1221 4
#@ maskGaps also operates on columns and will mask collumns based on the fraction of each column that contains gaps min.fraction along with the width of columns that contain this fraction of gaps min.block.width.
autoMasked <- maskGaps(origMAlign, min.fraction=0.5, min.block.width=4)
autoMasked
DNAMultipleAlignment with 8 rows and 2343 columns
aln names
[1] ###################################################…################################################## Human
[2] ###################################################…################################################## Chimp
[3] ###################################################…################################################## Cow
[4] ###################################################…################################################## Mouse
[5] ###################################################…################################################## Rat
[6] ###################################################…################################################## Dog
[7] ###################################################…################################################## Chicken
[8] ###################################################…################################################## Salmon
#@ Sometimes you may want to cast your MultipleAlignment to be a matrix for usage eslewhere. as.matrix is supported for these circumstances. The ability to convert one object into another is not very unusual so why mention it? Because when you cast your object, the masks WILL be considered so that the masked rows and columns will be left out of the matrix object.
full <- as.matrix(origMAlign)
dim(full)
[1] 8 2343
partial <- as.matrix(autoMasked)
dim(partial)
#@ One example of where you might want to use as.matrix is when using the ape package. For example if you needed to use the dist.dna function you would want to use as.matrix followed by as.alignment and then the as.DNAbin to create a DNAbin object for the dist.dna.
3.3 Analytic utilities
Once you have masked the sequence, you can then ask questions about the properties of that sequence. For
example, you can look at the alphabet frequency of that sequence. The alphabet frequency will only be for
the masked sequence.
alphabetFrequency(autoMasked)
A C G T M R W S Y K V H D B N - + .
[1,] 260 351 296 218 0 0 0 0 0 0 0 0 0 0 0 18 0 0
[2,] 171 271 231 128 0 0 0 0 0 0 0 0 0 0 3 339 0 0
[3,] 277 360 275 209 0 0 0 0 0 0 0 0 0 0 0 22 0 0
[4,] 265 343 277 226 0 0 0 0 0 0 0 0 0 0 0 32 0 0
[5,] 251 345 287 229 0 0 0 0 0 0 0 0 0 0 0 31 0 0
[6,] 160 285 241 118 0 0 0 0 0 0 0 0 0 0 0 339 0 0
[7,] 224 342 273 190 0 0 0 0 0 0 0 0 0 0 0 114 0 0
[8,] 268 289 273 262 0 0 0 0 0 0 0 0 0 0 0 51 0 0
#@ You can also calculate a consensus matrix, extract the consensus string or look at the consensus views. These methods too will all consider the masking when you run them.
consensusMatrix(autoMasked, baseOnly=TRUE)[, 84:90]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
A 0 3 0 3 0 3 3
C 3 0 0 1 1 1 2
G 1 2 4 1 2 0 0
T 1 0 1 0 1 1 0
other 3 3 3 3 4 3 3
substr(consensusString(autoMasked),80,130)
[1] “####CRGABAMGTCA-YRGCTTCTCYGTSCAWAGGCRRTGRCYTGTTYTCG”
consensusViews(autoMasked)
Views on a 2343-letter BString subject
subject: ----------------------VWVMKYYBSRSTSDYVVMDKBHSVGHKSMSVRYVKDR…-----------------------------------------------------------
views:
start end width
[1] 84 325 242 [CRGABAMGTCA-YRGCTTCTCYGTSCAWAGGCRRTGRCYTGTTYTCGYCCRR…GGARKCGYCSSCGSKGCCRSCCGAMWGCGSCTCSGCYGGSGCYRYCCTGSGG]
[2] 330 332 3 [CCR]
[3] 338 1191 854 [CTGCTGCTGYCGGGVCACGGCGYYCGG-GAMGCKCMCAGYCCC—GGGCCK…CTTTTCCYYTCASARW-KATTGGCTCTGMTAGTTTTTATGTATAAATATATA]
[4] 1198 1241 44 [ATAAAATATAAKAC–TTTTTATAYRSCARATGTAAAAATTCAA]
You can also cluster the alignments based on their distance to each other. Because you must pass in
a DNAStringSet, the clustering will also take into account the masking. So for example, you can see how
clustering the unmasked DNAMultipleAlignment will draw a funky looking tree.
sdist <- stringDist(as(origMAlign,“DNAStringSet”), method=“hamming”)
clust <- hclust(sdist, method = “single”)
pdf(file=“badTree.pdf”)
plot(clust)
dev.off()
#@ But, if we use the gap-masked DNAMultipleAlignment, to remove the long uninformative regions, and then make our plot, we can see the real relationships.
sdist <- stringDist(as(autoMasked,“DNAStringSet”), method=“hamming”)
clust <- hclust(sdist, method = “single”)
pdf(file=“goodTree.pdf”)
plot(clust)
dev.off()
fourgroups <- cutree(clust, 4)
fourgroups
Human Chimp Cow Mouse Rat Dog Chicken Salmon
1 2 1 1 1 2 3 4
In the “good” plot, the Salmon sequence is once again the most distant which is what we expect to
see. A closer examination of the sequence reveals that the similarity between the mouse, rat and human
sequences was being inflated by virtue of the fact that those sequences were simply much longer (had more
information than) the other species represented. This is what caused the “funky” result. The relationship
between the sequences in the funky tree was being driven by extra “length” in the rodent/mouse/human
sequences, instead of by the similarity of the conserved regions.
3.4 Exporting to file
One possible export option is to write to fasta files If you need to write your MultipleAlignment object out
as a fasta file, you can cast it to a DNAStringSet and then write it out as a fasta file like so:
DNAStr = as(origMAlign, “DNAStringSet”)
writeXStringSet(DNAStr, file=“myFile.fa”)
#@ One other format that is of interest is the Phylip format. The Phylip format sOne other format that is of interest is the Phylip format. The Phylip format stores the column masking of your object as well as the sequence that you are exporting. So if you have masked the sequence and you write out a Phylip file, this mask will be recorded into the file you export. As with the fasta example above, any rows that you have masked out will be removed from the exported file.
write.phylip(phylipMAlign, filepath=“myFile.txt”)
4.结束
sessionInfo()