Package 'NameNeedle'

Description

This dataset contains vectors of cell line names that are used to demonstrate how to use the NameNeedle package.

Usage

data(cellLineNames)

Format

This dataset contains four objects: three character vectors (sf2Names, rppaNames, and illuNames) and one factor (illuType).

Details

The three character vectors, sf2Names, rppaNames, and illuNames contain the names of cell lines used in three different but related experiments. The factor, illuType, indicates whether the cell lines named in the illuNames vector were derived from lung cancer (with the value "Lung") or from head and neck cancer ("HNSCC").

Examples

data(cellLineNames)
head(rppaNames)
head(sf2Names)
head(illuNames)
summary(illuType)

Description

The Needleman-Wunsch simple gap algorithm was one of the first methods introduced for global alignment of biological sequences. The same algorithm can be used to match cell line names or sample names from two related data sets; we provide examples in the documentation, using data that accompanies this package.

While the NameNeedle package can be used for biological sequence alignment, the Biostrings package from Bioconductor contains much more sophisticated tools for that problem.

Usage

needles(pattern, subject, params=defaultNeedleParams)
needleScores(pattern, subjects, params=defaultNeedleParams)
defaultNeedleParams

Arguments

   
    $ MATCH   : num 1
    $ MISMATCH: num -1
    $ GAP     : num -1
    $ GAPCHAR : chr "*"

Details

The Needleman-Wunsch global alignment algorithm was one of the first algorithms used to align DNA, RNA, or protein sequences. The basic algorithm uses dynamic programming to find an optimal alignment between two sequences, with parameters that specify penalties for mismatches and gaps and a reward for exact matches. More elaborate algorithms (not implemented here) make use of matrices with different penalties depending on different kinds of mismatches. The version implemented here is based on the Perl implementation in the first section of Chapter 3 of the book BLAST.

Value

The needles function returns a list with five components:

The needleScores function returns a numeric vector the same length as the subjects argument, with each entry equal to the corresponding raw alignment score.

Author(s)

Kevin R. Coombes [email protected], P. Roebuck [email protected]

References

Needleman SB, Wunsch CD.
A general method applicable to the search for similarities in the amino acid sequence of two proteins.
J Mol Biol 1970, 48(3):443–453.

Korf I, Yandell M, Bedell J.
BLAST.
O'Reilly Media, 2003.

Wang J, Byers LA, Yordy JS, Liu W, Shen L, Baggerly KA, Giri U, Myers JN, Ang KK, Story MD, Girard L, Minna JD, Heymach JV, Coombes KR.
Blasted cell line names.
Cancer Inform. 2010; 9:251–5.

See Also

The Biostrings package from Bioconductor used to contain a function called needwunQS that provided a simple gap implementation of Needleman-Wunsch, similar to the one presented here. That function has been deprecated in favor of a more elaborate interface called pairwiseAlignment that incorporates a variety of other alignment methods in addition. While pairwiseAlignment is much more useful for applications to biological sequences, it is serious overkill for the application we have in mind for matching cell line or other sample names.

Examples

data(cellLineNames)
myParam <- defaultNeedleParams
myParam$MATCH <- 2
myParam$MISMATCH <- -2
needles(sf2Names[2], illuNames[1], myParam)
scores <- needleScores(sf2Names[6], illuNames, myParam)
w <- which(scores == max(scores))
w
sf2Names[6]

needles(sf2Names[6], illuNames[w], myParam)