Title: Self Organising Maps for the Analysis of Molecular Dynamics Data
Version: 0.1.2
Description: Processes data from Molecular Dynamics simulations using Self Organising Maps. Features include the ability to read different input formats. Trajectories can be analysed to identify groups of important frames. Output visualisation can be generated for maps and pathways. Methodological details can be found in Motta S et al (2022) <doi:10.1021/acs.jctc.1c01163>. I/O functions for xtc format files were implemented using the 'xdrfile' library available under open source license. The relevant information can be found in inst/COPYRIGHT.
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.3.2
Depends: R (≥ 3.5.0)
Imports: bio3d, kohonen, abind, cluster, methods, igraph
Suggests: testthat (≥ 3.0.0)
Config/testthat/edition: 3
NeedsCompilation: yes
Packaged: 2024-10-01 07:52:26 UTC; apandini
Author: Alessandro Pandini ORCID iD [aut, cph], Stefano Motta ORCID iD [aut, cre, cph], Erik Lindahl [ctb] (Author of xdrfile C library), David van der Spoel [ctb] (Author of xdrfile C library)
Maintainer: Stefano Motta <stefano.motta@unimib.it>
Repository: CRAN
Date/Publication: 2024-10-02 13:50:06 UTC

Compute average property

Description

Function to compute the average value of a property for each neuron.

Usage

average.neur.property(SOM, P)

Arguments

SOM

the SOM object to cluster

P

the property for each frame of the simulation

Value

The a vector with the per-neuron average of the property.

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

#Read trajectory
trj <- read.trj(trjfile = system.file("extdata", "HIF2a-MD.xtc", package = "SOMMD"),
  topfile = system.file("extdata", "HIF2a.gro", package = "SOMMD"))
#Read example SOM data
som_model <- readRDS(system.file("extdata", "SOM_HIFa.rds", package = "SOMMD"))
#Compute distance between two atoms in every frame of the simulation
Distance <- apply(trj$coord[c(162,1794),,], 3, dist)
#Compute average property value for each neuron
avg.p <- average.neur.property(som_model, Distance)

calc.distances

Description

Function to compute distances to be used to train the SOM

Usage

calc.distances(trj, mol.2 = FALSE, sele = FALSE, atoms = NULL, cap = NULL)

Arguments

trj

contains the trajectory coordinates (array with three dimensions obtained by rioxdr)

mol.2

contains the atom indexes of the second molecule in case only intermolecular distances should be computed

sele

contains the selection of distances coming from the native_contacts function

atoms

contains a list of atoms indexes on which the distances will be computed

cap

If a number is given, distances greater than this value are set at the cap value

Value

A matrix containing the set of distances computed for all the frames.

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

# Read reference structure file with native conformation
struct <- read.struct(system.file("extdata", "HIF2a.gro", package = "SOMMD"))
# Read the trajectory
trj <- read.trj(trjfile = system.file("extdata", "HIF2a-MD.xtc", package = "SOMMD"),
  topfile = system.file("extdata", "HIF2a.gro", package = "SOMMD"))
# Select only Cbeta atoms to perform the analysis
sele_atoms <- which(trj$top$elety=="CB")
# Choose only native contacts
sele_dists <- native.cont(struct=struct, distance=1.0, atoms=sele_atoms)
# Compute distances for SOM training.
DIST <- calc.distances(trj, mol.2=FALSE, sele=sele_dists, atoms=sele_atoms)

Calculation of Distances

Description

Compute the pairwise distance matrix of a given set of coordinates, and only retain to some selected distances

Usage

calc.dists(coord, mol.1_id = FALSE, mol.2_id = FALSE, sele = FALSE)

Arguments

coord

matrix of N atomic coordinates (N rows, 3 columns)

mol.1_id

vector containing the index of the first molecule for intermolecular distances only

mol.2_id

vector containing the index of the second molecule for intermolecular distances only

sele

contains the selection of distances coming from the native_contacts function

Value

A matrix contaning the selected distances for a frame

Author(s)

Stefano Mottastefano.motta@unimib.it

Concatenate simulations

Description

Function to concatenate two simulations.

Usage

cat.trj(trj1, ...)

Arguments

trj1

the first trj file

...

additional trj files

Value

A trj object with the simulations concatenated

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

# Read the simulations
trj1 <- read.trj(trjfile = system.file("extdata", "HIF2a-MD.xtc", package = "SOMMD"),
  topfile = system.file("extdata", "HIF2a.gro", package = "SOMMD"))
trj2 <- read.trj(trjfile = system.file("extdata", "HIF2a-MD-2.xtc", package = "SOMMD"),
  topfile = system.file("extdata", "HIF2a.gro", package = "SOMMD"))
# Concatenate the simulations
  trj <- cat.trj(trj1, trj2)

Clustering of Pathways

Description

Cluster pathways according to a time dependent or independent scheme

Usage

cluster.pathways(
  SOM,
  start,
  end,
  time.dep = "independent",
  method = "complete"
)

Arguments

SOM

a kohonen SOM object.

start

the vector specifying the starting frame of each replicas

end

the vector specifying the ending frame of each replicas

time.dep

choose whether to use time "dependent" or "independent" clustering of pathways

method

the method to be passed to hclust for the clustering

Value

representatives a vector of frames representatives of each neuron

Author(s)

Stefano Mottastefano.motta@unimib.it

Examples

#Read trajectory
trj <- read.trj(trjfile = system.file("extdata", "HIF2a-MD.xtc", package = "SOMMD"),
  topfile = system.file("extdata", "HIF2a.gro", package = "SOMMD"))
#Assign length of the replicas
trj$start <- seq(1, 25, by=5)
trj$end <- seq(5, 25, by=5)
#Read example SOM data
som_model <- readRDS(system.file("extdata", "SOM_HIFa.rds", package = "SOMMD"))
#Cluster Pathways using the time dependent algorithm
clus.paths.tdep <- cluster.pathways(som_model, start=trj$start, end=trj$end,
  time.dep="dependent")
#Cluster Pathways using the time independent algorithm
clus.paths.tindep <- cluster.pathways(som_model,
  start=trj$start, end=trj$end, time.dep="independent")

Cluster Representatives

Description

Compute the cluster representatives

Usage

cluster.representatives(SOM, clusters)

Arguments

SOM

a kohonen SOM object.

clusters

a vector of clusters assignment for each neuron, as returned for example by hclust.

Value

A vector of frames representatives of each neuron

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

#Read example SOM data
som_model <- readRDS(system.file("extdata", "SOM_HIFa.rds", package = "SOMMD"))
# Divide the SOM in the selected number of clusters
som_cl <- cutree(hclust(dist(som_model$codes[[1]], method="euclidean"), method="complete"), 4)
#Get representative frames for each cluster
cl_repres <- cluster.representatives(som_model, som_cl)

Compute transition matrix

Description

Compute the transition matrix starting from a vector of subsequent classifications

Usage

comp.trans.mat(SOM, start = 1)

Arguments

SOM

a kohonen object on which transitions between neurons will be computed

start

a vector containing the start frames of each replica (usually contained in trj$start if replicas were merged with cat_trj)

Value

A matrix of pairwise transitions between neurons

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

#Read example SOM data
som_model <- readRDS(system.file("extdata", "SOM_HIFa.rds", package = "SOMMD"))
#Compute transition Matrix
tr_mat <- comp.trans.mat(som_model, start = 1)

Coordinate superposition

Description

Coordinate superposition with the Kabsch algorithm. This function make use of the bio3d fit.xyz function to align a SOMMD trj object. If ref is not specified, the trj object is aligned to the first frame of the simulation, otherwise it is aligned to the reference input object.

Usage

fit.trj(trj, ref = NULL, trj.inds = NULL, ref.inds = NULL)

Arguments

trj

an object with class trj

ref

a struct object read with read.struct() to be used as reference

trj.inds

a vector of indices that selects the trj atoms upon which fitting should be based. If not specified all atoms will be used.

ref.inds

a vector of indices that selects the ref atoms upon which fitting should be based. If not specified all atoms will be used.

Value

A trj object aligned

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

#Read trajectory
trj <- read.trj(trjfile = system.file("extdata", "HIF2a-MD.xtc", package = "SOMMD"),
  topfile = system.file("extdata", "HIF2a.gro", package = "SOMMD"))
# Fit a trajectory to the first frame based on alpha carbons:
ca.inds <- which(trj$top$elety=="CA")
trj.fit <- fit.trj(trj, trj.inds=ca.inds)

Map the property vector to colours

Description

Function map a numeric vector of a property to a vector of colors for that property according to that property value.

Usage

map.color(x, pal, limits = NULL, na.col = "grey")

Arguments

x

a numeric vector

pal

a color palette

limits

the values of the extremes for the colorscale

na.col

the color that will be assigned to the na.values of the vector

Value

A vector with colors proportional to the values of x

Convert transition matrix to an igraph object

Description

Function to convert a transition matrix to an igraph object

Usage

matrix2graph(trans, SOM, SOM.hc, col.set, diag = FALSE)

Arguments

trans

a transition matrix (usually obtained from comp.trans.mat)

SOM

a kohonen object that form the network

SOM.hc

a vector of cluster assignment for SOM neurons

col.set

a vector of colors used for the SOM clusters

diag

boolean condition to include diagonal elements

Value

An igraph object, with SOM properties annotated

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

#Read example SOM data
som_model <- readRDS(system.file("extdata", "SOM_HIFa.rds", package = "SOMMD"))
#Divide the SOM in the selected number of clusters
som_cl <- cutree(hclust(dist(som_model$codes[[1]], method="euclidean"), method="complete"), 4)
#Compute transition matrix
tr_mat <- comp.trans.mat(som_model, start = 1)
#Define a set of colors
colors <- c("#1f78b4", "#33a02c", "#e31a1c", "#ffff88", "#6a3d9a")
#Create graph object
net <- matrix2graph(tr_mat, som_model, som_cl, colors, diag=FALSE)

Select native contact distances

Description

Function to select only distances between residues making contacts in reference file or a frame of the simulation

Usage

native.cont(
  struct = NULL,
  trj = NULL,
  trj.frame = 1,
  distance,
  mol.2 = FALSE,
  atoms = NULL
)

Arguments

struct

a struct object read with read.struct() to compute the native.cont

trj

a trj object to compute the native.cont

trj.frame

The frame of the trj on which the native.cont are computed

distance

the distance cut-off

mol.2

can be FALSE (default), use the whole distance matrix, or a vector containing the atomic number of the second molecule (and compute only intermolecular distances)

atoms

can be NULL (default), consider all the atoms present in coords, or a vector containing a set of atomic numbers to consider in the calculation (e.g. only CB). atoms can be obtained with the bio3d atom.select function

Value

A vector containing the index of a subset of selected distances

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

# Read reference structure file with native conformation
struct <- read.struct(system.file("extdata", "HIF2a.gro", package = "SOMMD"))
#Select only Cbeta atoms to perform the analysis
sele_atoms <- which(struct$atom$elety=="CB")
#Choose only native contacts
sele_dists <- native.cont(struct=struct, distance=1.0, atoms=sele_atoms)

Get Neuron Population

Description

Function to compute the per-neuron population

Usage

neur.population(SOM, start = 1, end = length(SOM$unit.classif), N = 1)

Arguments

SOM

the SOM object

start

a vector containing the start frames of each replica (usually contained in trj$start if replicas were merged with cat_trj)

end

a vector containing the end frames of each replica (usually contained in trj$end if replicas were merged with cat_trj)

N

An integer for the portion (replica) of the simulations to be plotted

Value

A vector containing the per-neuron population

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

#Read example SOM data
som_model <- readRDS(system.file("extdata", "SOM_HIFa.rds", package = "SOMMD"))
pop <- neur.population(som_model)

Neuron representative

Description

Compute the representative frame of each neuron (the closest to the neuron codebook)

Usage

neur.representatives(SOM)

Arguments

SOM

a kohonen SOM object.

Value

A vector containing the index of the representative frames for each neuron

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

#Read example SOM data
som_model <- readRDS(system.file("extdata", "SOM_HIFa.rds", package = "SOMMD"))
#Compute representative frame for each neuron
neuron_representatives <- neur.representatives(som_model)

print.struct

Description

A short description...

Usage

## S3 method for class 'struct'
print(x, ...)

Arguments

x

trj object

...

additional arguments to be passed to further methods

Value

Called for its effect.

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

# Read structure file
struct <- read.struct(system.file("extdata", "HIF2a.gro", package = "SOMMD"))
#Print basic information
print(struct)

Print Trajectory

Description

A short description...

Usage

## S3 method for class 'trj'
print(x, ...)

Arguments

x

trj object

...

additional arguments to be passed to further methods

Value

Called for its effect.

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

#Read trajectory
trj <- read.trj(trjfile = system.file("extdata", "HIF2a-MD.xtc", package = "SOMMD"),
  topfile = system.file("extdata", "HIF2a.gro", package = "SOMMD"))
#Print basic informations
print(trj)

Read gro file

Description

Function to read gro files

Usage

read.gro(file)

Arguments

file

contains the name and the path to the gro file to be read

Value

Returns a list of class "gro" with the following components:

atom

a data frame containing all atomic coordinate with a row per atom and a column per record type.

xyz

a numeric matrix of class "xyz" containing the atomic coordinate data.

box

a vector of box size.

call

the matched call.

Author(s)

Stefano Motta stefano.motta@unimib.it

Read structure files

Description

Function to read pdb and gro files

Usage

read.struct(file)

Arguments

file

contains the name and the path to the pdb or gro file to be read

Value

Returns a list of class "struct" with the following components:

atom

a data frame containing all atomic coordinate with a row per atom and a column per record type.

xyz

a numeric matrix of class "xyz" containing the atomic coordinate data.

box

a vector of box size.

format

The format of the original file

call

the matched call.

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

# Read structure file
struct <- read.struct(system.file("extdata", "HIF2a.gro", package = "SOMMD"))

Read trj file

Description

Function to read a trajectory file

Usage

read.trj(trjfile, topfile)

Arguments

trjfile

contains the name and the path to the reference file (pdb or gro files are accepted)

topfile

contains the name and the path to the trajectory file (xtc or dcd files are accepted)

Value

Returns a list of class "trj" with the following components:

topfile

the input topology file.

topformat

the format of the input topology.

trjfile

the input trajectory file.

trjformat

the format of the input trajectory.

coord

a three dimensional array containing atomic coordinates for all the frames. Dimensions are: Natoms:3:Nframes.

top

a data.frame containing topological informations with a row per atom and a column per record type (resno, resid, elety, eleno, chain).

start

a vector with the first frame of the simulation. When multiple simulations are concatenated with cat.trj the vector indicates the first frame of each simulation.

end

a vector with the last frame of the simulation. When multiple simulations are concatenated with cat.trj the vector indicates the last frame of each simulation.

call

the matched call.

Author(s)

Alessandro Pandini

Examples

#Read trajectory
trj <- read.trj(trjfile = system.file("extdata", "HIF2a-MD.xtc", package = "SOMMD"),
  topfile = system.file("extdata", "HIF2a.gro", package = "SOMMD"))

map data to existing SOM

Description

Assign new data to a pre-trained SOM

Usage

remap.data(SOM, X, add = FALSE)

Arguments

SOM

a trained SOM

X

a data set with the same number of features of the dataset used to train the SOM

add

whether to append the new data to the ones used to train the SOM

Value

An object of class "kohonen" with the new data mapped

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

#Read example SOM data
som_model <- readRDS(system.file("extdata", "SOM_HIFa.rds", package = "SOMMD"))
#Read a trajectory that was not used to train the som
trj_2 <- read.trj(trjfile = system.file("extdata", "HIF2a-MD-2.xtc", package = "SOMMD"),
  topfile = system.file("extdata", "HIF2a.gro", package = "SOMMD"))
#Read reference structure file
gro <- read.struct(system.file("extdata", "HIF2a.gro", package = "SOMMD"))
#Selection of the same intermolecular distances used to train the SOM
protein.sele <- which(gro$atom$resid!="020")
ligand.sele <- which(gro$atom$resid=="020")
heavy.atoms <- which(startsWith(gro$atom$elety, "H")==FALSE)
sele.dists <- native.cont(struct=gro, distance=0.6, mol.2=ligand.sele, atoms=heavy.atoms)
# Compute distances on new simulations (the same used for SOM training)
dist_2 <- calc.distances(trj_2, mol.2=ligand.sele, sele=sele.dists, atoms=heavy.atoms)
# Map new data on the existing SOM
som_model_2 <- remap.data(SOM=som_model, X=dist_2)

Read xtc trajectory file

Description

Function to read an xtc trajectory file

Usage

rio_read_xtc(xtc_filename)

Arguments

xtc_filename

contains the name and the path to the xtc file

Value

Returns 3D array of cartesian coordinates

Author(s)

Alessandro Pandini

Read xtc trajectory file

Description

Function to read an xtc trajectory file

Usage

rio_read_xtc2xyz(xtc_filename)

Arguments

xtc_filename

contains the name and the path to the xtc file

Value

Returns bio3d xyz array of Cartesian coordinates

Author(s)

Alessandro Pandini

Read xtc trajectory file

Description

Function to read a xtc trajectory file

Usage

rio_read_xtc_natoms(xtc_filename)

Arguments

xtc_filename

contains the name and the path to the xtc file

Value

Returns number of atoms in the structure

Author(s)

Alessandro Pandini

Read xtc trajectory file

Description

Function to read an xtc trajectory file

Usage

rio_read_xtc_nframes(xtc_filename)

Arguments

xtc_filename

contains the name and the path to the xtc file

Value

Returns number of frames in the trajectory

Author(s)

Alessandro Pandini

Write xtc trajectory file

Description

Function to write an xtc trajectory file

Usage

rio_write_xtc(xtc_filename, trj)

Arguments

xtc_filename

contains the name and the path to the xtc file to write

trj

trajectory object to save

Value

Returns status of write execution

Author(s)

Alessandro Pandini

Silhouette profile

Description

Function to compute the silhouette profile for the Nclus cluster of the SOM neurons

Usage

silhouette.profile(
  SOM,
  Nclus,
  dist_clust = "euclidean",
  clust_method = "complete"
)

Arguments

SOM

the SOM object to cluster

Nclus

the cluster number on which the silhouette profile will be computed

dist_clust

the metric for the distance calculation

clust_method

the method for the clustering (passed to the hclust function

Value

A vector of silhouette profile computed with the cluster package

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

#Read example SOM data
som_model <- readRDS(system.file("extdata", "SOM_HIFa.rds", package = "SOMMD"))
#Compute the silhouette profile
sil_pro <- silhouette.profile(som_model, Nclus=5, clust_method="complete")

Silhouette score

Description

Function to compute the silhouette score for the clustering of SOM neurons

Usage

silhouette.score(
  SOM,
  dist_clust = "euclidean",
  clust_method = "complete",
  interval = seq(2, 30)
)

Arguments

SOM

the SOM object to cluster

dist_clust

the metric for the distance calculation

clust_method

the method for the clustering (passed to the hclust function

interval

the cluster number on which the silhouette score will be computed

Value

A vector with the silhouette scores for all the frames

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

#Read example SOM data
som_model <- readRDS(system.file("extdata", "SOM_HIFa.rds", package = "SOMMD"))
#Compute the silhouette profile
sil_score <- silhouette.score(som_model, clust_method="complete", interval=seq(2,8))

Add circles to SOM

Description

Function to add circles to a SOM plot, with dimension proportional to a selected property

Usage

som.add.circles(SOM, P, scale = 1, col.circles = "white")

Arguments

SOM

the SOM object

P

a vector containing the per-neuron property to plot

scale

a number to scale up or down the size of the drawn circles

col.circles

the background color of the drawn circles

Value

Called for its effect.

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

#Read example SOM data
som_model <- readRDS(system.file("extdata", "SOM_HIFa.rds", package = "SOMMD"))
# Compute per neuron population
pop <- neur.population(som_model)
#Plot the som
plot(som_model, type = "count", bgcol=c("red", "blue", "yellow", "green"), shape='straight')
# Add circles to the SOM plot
som.add.circles(som_model, pop, scale=0.9)

Add legend clusters

Description

Function to apply a legend of clusters to a SOM map image

Usage

som.add.clusters.legend(Nclus, color.scale)

Arguments

Nclus

the number of clusters to which put the legent

color.scale

the color scale used for the image

Value

Called for its effect.

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

#Read example SOM data
som_model <- readRDS(system.file("extdata", "SOM_HIFa.rds", package = "SOMMD"))
#Divide the SOM in the selected number of clusters
som_cl <- cutree(hclust(dist(som_model$codes[[1]], method="euclidean"), method="complete"), 4)
#Define a set of colors
colors <- c("#1f78b4", "#33a02c", "#e31a1c", "#ffff88", "#6a3d9a") 
#Plot the som with neurons colored according to clusters
plot(som_model, type = "mapping", bgcol=colors[som_cl], col=rgb(0,0,0,0), shape='straight', main="")
kohonen::add.cluster.boundaries(som_model, som_cl, lwd=5)
#Add legend to the plot
som.add.clusters.legend(Nclus=4, color.scale=colors)

Add Neuron Numbering

Description

Add the neuron numbering scheme to the SOM plot

Usage

som.add.numbers(SOM, scale = 1, col = "black")

Arguments

SOM

the SOM object

scale

a number to scale up or down the size of the text

col

the color of the text

Value

Called for its effect.

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

#Read example SOM data
som_model <- readRDS(system.file("extdata", "SOM_HIFa.rds", package = "SOMMD"))
#Plot the som
plot(som_model, type = "count", bgcol=c("red", "blue", "yellow", "green"), shape='straight')
#Add neuron numbers on the som
som.add.numbers(som_model, scale=0.5, col="black")

Stride a trj

Description

Apply a stride to the frame of a trj object to reduce the number of frames

Usage

stride.trj(trj, stride)

Arguments

trj

a trj object.

stride

the stride to apply to the trajectory

Value

An object of class trj with a frame every stride

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

# Read the simulation
trj <- read.trj(trjfile = system.file("extdata", "HIF2a-MD.xtc", package = "SOMMD"),
  topfile = system.file("extdata", "HIF2a.gro", package = "SOMMD"))
# keep a frame every 2 frame
trj_strd <- stride.trj(trj, 2)

Convert structure to pdb object

Description

Convert a struct object into a pdb obtect

Usage

struct2pdb(struct)

Arguments

struct

contains the struct object to convert

Value

Returns an object with class "pdb"

An object of class "pdb"

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

# Read structure file 
struct <- read.struct(system.file("extdata", "HIF2a.gro", package = "SOMMD"))
#Convert structure to pdb object
pdb <- struct2pdb(struct)

Summarizing a structure object

Description

summary method for class struct

Usage

## S3 method for class 'struct'
summary(object, ...)

Arguments

object

struct object

...

additional arguments to be passed to further methods

Value

Called for its effect.

Author(s)

Stefano Motta stefano.motta@unimib.it

Summarizing a trajectory object

Description

summary method for class trj

Usage

## S3 method for class 'trj'
summary(object, ...)

Arguments

object

trajectory object

...

additional arguments to be passed to further methods

Value

Called for its effect.

Author(s)

Stefano Motta stefano.motta@unimib.it

Trace pathway

Description

Function trace pathway sampled on the SOM

Usage

trace.path(
  SOM,
  start = 1,
  end = length(SOM$unit.classif),
  N = 1,
  draw.stride = 1,
  pts.scale = 1,
  lwd.scale = 1
)

Arguments

SOM

the SOM object

start

a vector containing the start frames of each replica (usually contained in trj$start if replicas were merged with cat_trj)

end

a vector containing the end frames of each replica (usually contained in trj$end if replicas were merged with cat_trj)

N

The portion of simulation that one want to plot

draw.stride

used to plot the pathways with a stride (useful for very complex pathways)

pts.scale

a number to scale up or down the size of the circles

lwd.scale

a number to scale up or down the size of the lines

Value

Called for its effect.

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

# Read the trajectory
trj <- read.trj(trjfile = system.file("extdata", "HIF2a-MD.xtc", package = "SOMMD"),
  topfile = system.file("extdata", "HIF2a.gro", package = "SOMMD"))
#Read example SOM data
som_model <- readRDS(system.file("extdata", "SOM_HIFa.rds", package = "SOMMD"))
#trace pathway sampled on the SOM
trace.path(som_model, start=trj$start, end=trj$end, N=1, pts.scale=0.5)

Extract frame to pdb

Description

Extract a trj frame to a pdb object

Usage

trj2pdb(trj, frame, filename)

Arguments

trj

a trj object.

frame

the frame to extract.

filename

for the output pdb file

Value

a pdb object of the selected frame

Called for its effect.

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples


# Read the trajectory
trj <- read.trj(trjfile = system.file("extdata", "HIF2a-MD.xtc", package = "SOMMD"),
  topfile = system.file("extdata", "HIF2a.gro", package = "SOMMD"))
# Write the pdb file for a specific frame
trj2pdb(trj = trj, frame=5, filename = tempfile(fileext = '.pdb' ))

Convert Trajectory to xyz

Description

Convert the trj coordinates 3D-array in a 2D matrix.

Usage

trj2xyz(trj, inds = NULL)

Arguments

trj

an object with class trj

inds

indices for the output coordinates

Value

a xyz matrix with frames on rows and coordinates as columns

Author(s)

Stefano Motta stefano.motta@unimib.it

Examples

#Read trajectory
trj <- read.trj(trjfile = system.file("extdata", "HIF2a-MD.xtc", package = "SOMMD"),
  topfile = system.file("extdata", "HIF2a.gro", package = "SOMMD"))
trj2xyz(trj)