reverseComplement {Biostrings} | R Documentation |
These functions can reverse a BString, DNAString or RNAString object and complement each base of a DNAString object.
reverse(x, ...) complement(x, ...) reverseComplement(x, ...)
x |
A BString (or derived) object
or a BStringViews object for reverse .
A DNAString object
or a BStringViews object
with a DNAString subject for complement
and reverseComplement .
|
... |
Additional arguments to be passed to or from methods. |
Given an object x
of class BString, DNAString
or RNAString, reverse(x)
returns an object of the same class
where letters in x
are reordered in the reverse ordered.
If x
is a DNAString object, complement(x)
returns
an object where each base in x
is "complemented" i.e.
A, C, G, T are replaced by T, G, C, A respectively.
Letters belonging to the "IUPAC extended genetic alphabet"
are also replaced by their complement (M <-> K, R <-> Y, S <-> S, V <-> B,
W <-> W, H <-> D, N <-> N) and the gap symbol (-) is unchanged.
reverseComplement(x)
is equivalent to reverse(complement(x))
but is faster and more memory efficient.
An object of the same class and length as the original object.
reverseComplement(DNAString("ACGT-YN-")) ## Applying reverseComplement() to the pattern before calling matchPattern() ## is the standard way to search hits on the reverse strand of a chromosome: library(BSgenome.Dmelanogaster.FlyBase.r51) chrX <- Dmelanogaster[["X"]] pattern <- DNAString("GAACGGTGTCT") matchPattern(pattern, chrX) # 1 hit on strand + m0 <- matchPattern(reverseComplement(pattern), chrX) # 2 hits on strand - ## Applying reverseComplement() to the subject instead of the pattern is not ## a good idea for 2 reasons: ## (1) Chromosome sequences are generally huge so it's going to be a lot of ## work and require a lot of memory to compute reverseComplement(subject). ## (2) Chromosome locations are generally given relatively to the positive ## strand, even for features located in the negative strand, so after ## doing this: m1 <- matchPattern(pattern, reverseComplement(chrX)) ## the start/end of the matches are now relative to the negative strand. ## You need to apply reverseComplement() again on the result if you want ## them to be relative to the positive strand: m2 <- reverseComplement(m1) ## and finally to apply rev() to sort the matches from left to right ## (5'3' direction) like in m0: m3 <- rev(m2) # same as m0, finally! ## Don't try the above example on human chromosome 1 since your computer ## would need to allocate about 250Mb of memory for this: if (FALSE) { library(BSgenome.Hsapiens.UCSC.hg18) chr1 <- Hsapiens$chr1 matchPattern(pattern, reverseComplement(chr1)) # DON'T DO THIS! matchPattern(reverseComplement(pattern), chr1) # DO THIS INSTEAD }