buildFeatureVector {cleanUpdTSeq} | R Documentation

## buildFeatureVector

### Description

This function creates a data frame. Fields include peak name, upstream sequence, downstream sequence, and features to be used in classifying the putative polyadenylation site.

### Usage

    buildFeatureVector(peaks, BSgenomeName = Drerio, upstream = 50L,
    	downstream = 40L, wordSize = 6L, alphabet = c("ACGT"),
     sampleType = c("TP", "TN", "unknown"), replaceNAdistance = 40L,
     method = c("NaiveBayes", "SVM"), ZeroBasedIndex = 1L, fetchSeq = FALSE)

### Arguments

`peaks` | An object of GRanges that may contain the upstream and downstream sequence information. This item is created by the function BED2GRangesSeq.
`BSgenomeName` | Name of the genome to use to get sequence. To find out a list of available genomes, please type available.genomes() in R.
`upstream` | This is the length of upstream sequence to use in the analysis.
`downstream` | This is the length of downstream sequence to use in the analysis.
`wordSize` | This is the size of the word to use as a feature for the upstream sequence. wordSize = 6 should always be used.
`alphabet` | These are the bases to use, for example DNA bases ACTG.
`sampleType` | This is the type of sample. For example TP (true positive) or TN (true negative) for training data or unknown for test data.
`replaceNAdistance` | If there is no A in the downstream sequence, then use this for the average distance of As to the putative polyadenylation site.
`method` | This is which machine learning method to specify. For this release, method should always be set to NaiveBayes.
`ZeroBasedIndex` | If the coordinates are set using Zero Based indexing, set this = 1.
`fetchSeq` | Boolean, for getting upstream and downstream sequence at this step or not.

### Value

An object of "`featureVector`"

### Author(s)

Sarah Sheppard, Jianhong Ou, Nathan Lawson, Lihua Julie Zhu

### Examples

    testFile = system.file("extdata", "test.bed", package="cleanUpdTSeq")
    testSet = read.table(testFile, sep = "\t", header = TRUE)

    #convert the test set to GRanges with upstream and downstream sequence information
    peaks = BED2GRangesSeq(testSet[1:10, ], upstream.seq.ind = 7, downstream.seq.ind = 8, withSeq=TRUE)
    #build the feature vector for the test set with sequence information
    library(BSgenome.Drerio.UCSC.danRer7)
    testSet.NaiveBayes = buildFeatureVector(peaks,BSgenomeName = Drerio, upstream = 40,
    	   downstream = 30, wordSize = 6, alphabet=c("ACGT"),
    	   sampleType = "unknown",replaceNAdistance = 30,
    	   method = "NaiveBayes", ZeroBasedIndex = 1, fetchSeq = FALSE)

    #convert the test set to GRanges without upstream and downstream sequence information
    peaks = BED2GRangesSeq(testSet[1:10, ],withSeq=FALSE)

    #build the feature vector for the test set without sequence information
    testSet.NaiveBayes = buildFeatureVector(peaks,BSgenomeName = Drerio, upstream = 40,
            downstream = 30, wordSize = 6, alphabet=c("ACGT"),
            sampleType = "unknown",replaceNAdistance = 30,
            method = "NaiveBayes", ZeroBasedIndex = 1, fetchSeq = TRUE)

[Package cleanUpdTSeq version 1.24.0 Index]