write.scores | R Documentation |
Given a correlation object, writes the score, the Zscore and, optionally the entropy, for each pair of elements in a csv file.
write.scores(correlation, filepathroot, entropy= NULL)
correlation |
An object created by a correlation/covariation function ( |
entropy |
An object created by the |
filepathroot |
The root of the full path name for the output file. DEfault is NULL, a "CORR_SCORES.csv" file is created in tempdir(). If not NULL, the "_CORR_SCORES.csv" extension is added to the filepathroot. |
Elements represent positions in multiple sequence alignments and side chain dihedral angles in molecular dynamic simulations (MD).
In sequence analysis, the correlation object contains two matrices with the correlation/covariation scores and Z-scores for each pair of elements [i,j]. If entropy = NULL, each line of the output file will contain element i, element j, score[i,j], and Z-score[i,j]. If entropy is not NULL, each line of the output file will contain element i, element j, score[i,j], Zscore[i,j], entropy[i], and entropy[j].
In MD analysis, the correlation object contains four matrices with (1) the correlation/covariation scores for each pair of rotamers (score), (2) the Z-scores for each pair of rotamers (Zscore), (3) the correlation/covariation scores for each pair of rotamers with zero values for autocorrelation (correlation within the same side chain) (score_noauto) and (4) the Z-scores calculated without autocorrelation pairs and zero values for autocorrelation pairs (Zscore_noauto). If entropy = NULL, each line of the output file will contain element i, element j, score[i,j], Zscore[i,j], score_noauto[i,j], and Zscore_noauto[i,j]. If entropy is not NULL, each line of the output file will contain element i, element j, score[i,j], Zscore[i,j], score_noauto[i,j], Zscore_noauto[i,j], entropy[i], and entropy[j].
A csv file containing the correlation/covariation scores and optionally the entropies.
Antoine GARNIER and Marie CHABBERT
#Example for MSA
#File path for output files
out <- tempdir()
file <- file.path(out,"test_seq")
#Importing MSA file
msf <- system.file("msa/toy_align.msf", package = "Bios2cor")
align <- import.msf(msf)
#Creating correlation and entropy objects
correlation <- omes(align, gap_ratio= 0.2)
entropy <- entropy(align)
#Writing results to csv file
write.scores(correlation, file, entropy )
###Example for MD
#File path for output files
wd <- tempdir()
#wd <-getwd()
file <- file.path(wd,"test_dyn")
#Reading the pdb and dcd files and the angles to rotamers conversion file
pdb <- system.file("rotamer/toy_coordinates.pdb", package= "Bios2cor")
trj <- system.file("rotamer/toy_dynamics.dcd", package= "Bios2cor")
conversion_file <- system.file("rotamer/dynameomics_rotamers.csv", package= "Bios2cor")
#Creating dynamic_structure and rotamers objects
wanted_frames <- seq(from = 5, to = 40, by = 10)
dynamic_structure <- dynamic_structure(pdb, trj, wanted_frames)
rotamers <- angle2rotamer(dynamic_structure, conversion_file)
#Creating correlation and entropy objects
wanted_residues <- c("F","H","N","Y","W")
#dyn_corr <- dynamic_omes(dynamic_structure, rotamers, wanted_residues)
dyn_corr <- dynamic_circular(dynamic_structure, wanted_residues)
dyn_entropy <- dynamic_entropy(rotamers)
#Writing results to csv file
write.scores(dyn_corr, file, dyn_entropy )
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