funbarRF (version 1.0.2)

seq_funbarRF_manual: Conversion of barcode sequences manually collected from BOLD database into numeric features based on gap pair compositions.

Description

This function resulted in similar output as that of seq_funbarRF function. The only difference is in input sequences. To execute this function, the user has to collect the barcode sequences manually from the BOLD database and the same has to be supplied as input to this function.

Usage

seq_funbarRF_manual (manual_seq)

Arguments

manual_seq

Barcode sequences manually collected from the BOLD database.

Value

ref_label

Species labels of barcode sequences as factor.

ref_gpc

A matrix of dimension N*96, where N is the number of sequences and 96 columns represent the gap pair composition features for 0, 1, 2, 3, 4 and 5 gaps together.

Details

This function is a supplemnt to the seq_funbarRF function for mapping the manually collected barcode sequences from BOLD database into numeric feature vectors based on gap-pair compositional features.

References

1. Yu C.S., Chen Y.C., Lu C.H., and Hwang J.K. (2006). Prediction of protein subcellular localization. Proteins, 64(3), 643-651.

2. Meher P.K., Sahu T.K., Gahoi S., and Rao A.R. (2018). ir-HSP: Improved recognition of heat shock proteins, their families and sub-types based on g-spaced di-peptide features and support vector machine. Front. Genet., 8, 235.

3. Li H. (2016). BioSeqClass: Classification for biological Sequences. R package version 1.32.0.

See Also

seq_funbarRF, data_barcode, featureGapPairComposition

Examples

# NOT RUN {
data (data_barcode)
tr_ss <- seq_funbarRF_manual (manual_seq=data_barcode$Fish$train[1:2])
print (tr_ss$ref_label)
head (tr_ss$ref_gpc)
######################################

ts_ss <- seq_funbarRF_manual (manual_seq=data_barcode$Inga$test[1:2])
print (tr_ss$ref_label)
head (tr_ss$ref_gpc)


# }