lm.estimate: Linear Model Fitting
In GCAI.bias: Guided Correction Approach for Inherited bias (GCAI.bias)

Description Usage Arguments Details Value Author(s) References See Also Examples

To estimating the coefficients by fitting the linear model

1	lm.estimate(obj.train, fit.cut.train = 5)

`obj.train`	an object of training data generated from `index.preprocess` and `counts.preprocess`
`fit.cut.train`	the minimum counts of the data points used for model fitting, the default for spike-in training dataset is 5.

It models the influence on the local sequence from the dissimilarity of spike-in transcripts measurement. The region of positions around hexamer primers can be defined by the variable "word".

a 1-column matrix of coefficients will be returned.

Guoshuai Cai

Cai G, RNA-SEQUENCING APPLICATIONS: GENE EXPRESSION QUANTIFICATION AND METHYLATOR PHENOTYPE IDENTIFICATION, Ph.D. Thesis, 2013

index.preprocess,counts.preprocess

word<-81

data(train.dat.seq)
data(train.dat.counts)

train.index<-index.preprocess(train.dat.seq,word)
obj.train<-counts.preprocess(train.dat.counts)
obj.train[["index"]]<-train.index

coe.lm<-lm.estimate(obj.train,fit.cut.train=5)