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### Running command:
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### /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD build --keep-empty-dirs --no-resave-data --md5 TMixClust
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* checking for file ‘TMixClust/DESCRIPTION’ ... OK
* preparing ‘TMixClust’:
* checking DESCRIPTION meta-information ... OK
* installing the package to build vignettes
* creating vignettes ... ERROR
--- re-building ‘TMixClust.Rnw’ using knitr
TMixClust package:TMixClust R Documentation
_C_l_u_s_t_e_r_s _t_h_e _t_i_m_e _s_e_r_i_e_s _d_a_t_a _i_n _a _g_i_v_e_n _n_u_m_b_e_r _o_f _g_r_o_u_p_s
_D_e_s_c_r_i_p_t_i_o_n:
'TMixClust' is the central function of the package. It clusters
the given time series data into a specified number of clusters.
_U_s_a_g_e:
TMixClust(time_series_df, time_points = seq_len(ncol(time_series_df)),
nb_clusters = 2, em_iter_max = 1000, mc_em_iter_max = 10,
em_ll_convergence = 0.001)
_A_r_g_u_m_e_n_t_s:
time_series_df: data frame containing the time series. Each row is a
time series comprised of the time series name which is also
the row name, and the time series values at each time point.
time_points: vector containing numeric values for the time points.
Default: 'seq_len(ncol(time_series_df))'.
nb_clusters: desired number of clusters
em_iter_max: maximum number of iterations for the
expectation-maximization (EM) algorithm. Default: 1000.
mc_em_iter_max: maximum number of iterations for Monte-Carlo
resampling. Default is 100.
em_ll_convergence: convergence threshold for likelihood improvement.
Default is 0.001.
_V_a_l_u_e:
list object with the following attributes:
• 'em_gss_obj_list' object of class 'gss' containing estimated
parameters of the mixed-effects model (see package vignette
for more details).
• 'em_pi_k' vector containing the mixing coefficients
corresponding to each cluster
• 'em_mat_post' matrix containing the posterior values for each
time series and cluster
• 'em_cluster_assignment' vector with the clustering
attribution for each time series
• 'el_ll' vector containing the log likelihood values at each
iteration in the EM algorithm
• 'ts_data' the same as the input time series data-frame
• 'ts_time_points' the same as the input time-points vector
_A_u_t_h_o_r(_s):
Monica Golumbeanu, <mailto:monica.golumbeanu@bsse.ethz.ch>
_R_e_f_e_r_e_n_c_e_s:
Golumbeanu M, Desfarges S, Hernandez C, Quadroni M, Rato S,
Mohammadi P, Telenti A, Beerenwinkel N, Ciuffi A. (2017) Dynamics
of Proteo-Transcriptomic Response to HIV-1 Infection.
_E_x_a_m_p_l_e_s:
# Load the toy time series data provided with the TMixClust package
data(toy_data_df)
# Cluster the toy data with default parameters
TMixClust_obj = TMixClust(toy_data_df)
generate_TMixClust_report package:TMixClust R Documentation
_G_e_n_e_r_a_t_e_s _a _s_e_r_i_e_s _o_f _f_i_l_e_s _c_o_n_t_a_i_n_i_n_g _a _s_u_m_m_a_r_y _o_f _t_h_e _T_M_i_x_C_l_u_s_t
_a_n_a_l_y_s_i_s _r_e_s_u_l_t_s
_D_e_s_c_r_i_p_t_i_o_n:
'generate_TMixClust_report'
_U_s_a_g_e:
generate_TMixClust_report(TMixClust_object, report_folder = paste(getwd(),
"/TMixClust_report/", sep = ""), data_color = "#fd8d3c", x_label = "time",
y_label = "value")
_A_r_g_u_m_e_n_t_s:
TMixClust_object: list object created by the 'TMixClust' function (see
function 'TMixClust')
report_folder: full path of the folder where the report files will be
saved. Default is TMixClust_report/ folder in current working
directory.
data_color: color of the time series to be used when generating the
cluster plots. Default is orange.
x_label: label of the x axis for the cluster plots. Default is "time"
y_label: label of the y axis for the cluster plots. Default is "value"
_V_a_l_u_e:
Produces a series of files containing information about the
clustering results and saves them in the provided folder location.
The folder contains the following:
• 'log-lihelihood.txt' - file with the log likelihood values at
each iteration on separate lines
• 'log-likelihood.pdf' - plot of log-likelihood at each
iteration
• 'posterior.txt' - file with the posterior probabilities of
all the time-series for each cluster
• 'estimated_curves/' - folder containing a number of files
equal to the number of clusters; each file has 4 lines
consisting of curve values and their confidence intervals
(first 3 lines) for a discrete time grid (last line).
• 'clusters/' - folder containing a plot with the time series
in each cluster, a silhouette plot of the clustering
configuration, as well as, for each cluster, a file
containing the names of the time series in the respective
cluster and a file containing the names and time series
values for the time series in each cluster.
_A_u_t_h_o_r(_s):
Monica Golumbeanu, <mailto:monica.golumbeanu@bsse.ethz.ch>
_R_e_f_e_r_e_n_c_e_s:
Golumbeanu M, Desfarges S, Hernandez C, Quadroni M, Rato S,
Mohammadi P, Telenti A, Beerenwinkel N, Ciuffi A. (2017) Dynamics
of Proteo-Transcriptomic Response to HIV-1 Infection.
_E_x_a_m_p_l_e_s:
## Not run:
# Load the toy time series data provided with the TMixClust package
data(toy_data_df)
# Cluster the toy data with default parameters
TMixClust_obj = TMixClust(toy_data_df)
# Generate a TMixClust report in the current working directory
generate_TMixClust_report(TMixClust_obj)
## End(Not run)
get_time_series_df package:TMixClust R Documentation
_E_x_t_r_a_c_t_s _a _t_i_m_e _s_e_r_i_e_s _d_a_t_a _f_r_a_m_e _f_r_o_m _a _t_e_x_t _f_i_l_e
_D_e_s_c_r_i_p_t_i_o_n:
'get_time_series_df' creates a data frame containing time series
data from a file.
_U_s_a_g_e:
get_time_series_df(data_file)
_A_r_g_u_m_e_n_t_s:
data_file: path to a tab-delimited text file containing the time series
data formatted such that each row contains a time-series
represented by its name (e.g. gene name, protein name, etc.)
and the values at each time point.
_V_a_l_u_e:
A data frame containing the time series
_A_u_t_h_o_r(_s):
Monica Golumbeanu, <mailto:monica.golumbeanu@bsse.ethz.ch>
_R_e_f_e_r_e_n_c_e_s:
Golumbeanu M, Desfarges S, Hernandez C, Quadroni M, Rato S,
Mohammadi P, Telenti A, Beerenwinkel N, Ciuffi A. (2017) Dynamics
of Proteo-Transcriptomic Response to HIV-1 Infection.
_E_x_a_m_p_l_e_s:
# Load a simulated toy time-series data provided with the package
toy_data_file = system.file("extdata", "toy_time_series.txt",
package = "TMixClust")
toy_data= get_time_series_df(toy_data_file)
# Print the first lines of the resulting data frame
print(head(toy_data))
plot_time_series_df package:TMixClust R Documentation
_P_l_o_t_s _a_l_l _t_h_e _t_i_m_e _s_e_r_i_e_s _s_t_o_r_e_d _i_n _a _d_a_t_a _f_r_a_m_e _o_b_j_e_c_t
_D_e_s_c_r_i_p_t_i_o_n:
'plot_time_series_df' allows the user to visualise the time series
from a given data set.
_U_s_a_g_e:
plot_time_series_df(ts_df, time_points = seq_len(ncol(ts_df)),
data_color = "#fd8d3c", x_label = "time", y_label = "value",
plot_title = "Time series plot")
_A_r_g_u_m_e_n_t_s:
ts_df: data frame containing on each row a time-series
time_points: vector containing the values of the time points. Default:
'seq_len(ncol(time_series_df))'.
data_color: color of the time series to be used for the plot. Default
is orange.
x_label: label of the x axis of the plot. Default is "time"
y_label: label of the y axis of the plot. Default is "value"
plot_title: title of the plot. Default is "Time series plot".
_V_a_l_u_e:
Plots a figure with all the the time series in the data set
_A_u_t_h_o_r(_s):
Monica Golumbeanu, <mailto:monica.golumbeanu@bsse.ethz.ch>
_R_e_f_e_r_e_n_c_e_s:
Golumbeanu M, Desfarges S, Hernandez C, Quadroni M, Rato S,
Mohammadi P, Telenti A, Beerenwinkel N, Ciuffi A. (2017) Dynamics
of Proteo-Transcriptomic Response to HIV-1 Infection.
_E_x_a_m_p_l_e_s:
# Load the toy time series data provided with the TMixClust package
data(toy_data_df)
# Plot the time series
plot_time_series_df(toy_data_df)
plot_silhouette package:TMixClust R Documentation
_G_e_n_e_r_a_t_e_s _a _s_i_l_h_o_u_e_t_t_e _p_l_o_t _f_o_r _a _g_i_v_e_n _c_l_u_s_t_e_r_i_n_g _c_o_n_f_i_g_u_r_a_t_i_o_n.
_D_e_s_c_r_i_p_t_i_o_n:
'plot_silhouette'
_U_s_a_g_e:
plot_silhouette(TMixClust_object, sim_metric = "euclidean",
sil_color = "#bdbdbd")
_A_r_g_u_m_e_n_t_s:
TMixClust_object: list object created by the 'TMixClust' function (see
function 'TMixClust')
sim_metric: character string taking one of the possible values:
"euclidean", "gower" or "manhattan". Default is "euclidean".
sil_color: color of the bars representing the silhouette widths on the
plot
_V_a_l_u_e:
List object with the following components:
• 'similarity_m' similarity matrix
• 'silh' silhouette object
Renders a plot comprised of a set of barplots with the
distributions of silhouette coefficients for the data points in
each cluster. Each barplot has indicated on its right hand side
the total number of points in the corresponding cluster. The plot
also indicates with a dotted line, the overall average silhouette
width, whose value is specified at the bottom of the plot.
_A_u_t_h_o_r(_s):
Monica Golumbeanu, <mailto:monica.golumbeanu@bsse.ethz.ch>
_R_e_f_e_r_e_n_c_e_s:
Golumbeanu M, Desfarges S, Hernandez C, Quadroni M, Rato S,
Mohammadi P, Telenti A, Beerenwinkel N, Ciuffi A. (2017) Dynamics
of Proteo-Transcriptomic Response to HIV-1 Infection.
_E_x_a_m_p_l_e_s:
# Load the TMixClust object associated to the toy time series data
# provided with the TMixClust package
data(best_clust_toy_obj)
# Plot the silhouette for the clustering stored in the toy TMixClust object
plot_silhouette(best_clust_toy_obj)
analyse_stability package:TMixClust R Documentation
_S_t_a_b_i_l_i_t_y _a_n_a_l_y_s_i_s, _c_l_u_s_t_e_r_i_n_g _e_v_a_l_u_a_t_i_o_n _a_n_d _o_p_t_i_m_a_l _s_o_l_u_t_i_o_n
_s_e_l_e_c_t_i_o_n
_D_e_s_c_r_i_p_t_i_o_n:
'analyse_stability' Performs multiple clustering runs with
TMixClust, analyses the agreement between runs with the Rand index
and returns the clustering solution with the largest likelihood. A
plot of agreement probability between all the runs and the run
with the maximum likelihood is produced.
_U_s_a_g_e:
analyse_stability(time_series_df, time_points = seq_len(ncol(time_series_df)),
nb_clusters = 2, em_iter_max = 1000, mc_em_iter_max = 10,
em_ll_convergence = 0.001, nb_clustering_runs = 3, nb_cores = 1)
_A_r_g_u_m_e_n_t_s:
time_series_df: data frame containing the time series. Each row is a
time series comprised of the time series name which is also
the row name, and the time series values at each time point.
time_points: vector containing numeric values for the time points.
Default: 'seq_len(ncol(time_series_df))'.
nb_clusters: desired number of clusters
em_iter_max: maximum number of iterations for the
expectation-maximization (EM) algorithm. Default: 1000.
mc_em_iter_max: maximum number of iterations for Monte-Carlo
resampling. Default is 10.
em_ll_convergence: convergence threshold for likelihood improvement.
Default is 0.001.
nb_clustering_runs: number of times the clustering procedure is
repeated on the input data. Default is 3.
nb_cores: number of cores to be used to run the separate clustering
operations in parallel. Default is 1.
_V_a_l_u_e:
TMixClust object with the highest likelihood. Renders a plot
showing the overall distribution of the Rand index, which allows
the user to assess clustering stability.
_A_u_t_h_o_r(_s):
Monica Golumbeanu, <mailto:monica.golumbeanu@bsse.ethz.ch>
_R_e_f_e_r_e_n_c_e_s:
Golumbeanu M, Desfarges S, Hernandez C, Quadroni M, Rato S,
Mohammadi P, Telenti A, Beerenwinkel N, Ciuffi A. (2017) Dynamics
of Proteo-Transcriptomic Response to HIV-1 Infection.
_E_x_a_m_p_l_e_s:
# Load the toy time series data provided with the TMixClust package
data(toy_data_df)
# Identify the most optimal clustering solution with 3 clusters
best_clust_obj = analyse_stability(toy_data_df, nb_clusters = 3,
nb_clustering_runs = 4, nb_cores = 1)
# Plot the time series from each cluster
for (i in seq_len(3)) {
# Extract the time series in the current cluster and plot them
c_df=toy_data_df[which(best_clust_obj$em_cluster_assignment==i),]
plot_time_series_df(c_df, plot_title = paste("cluster",i))
}
Error: processing vignette 'TMixClust.Rnw' failed with diagnostics:
Running 'texi2dvi' on 'TMixClust.tex' failed.
LaTeX errors:
! Package xcolor Error: Undefined color `fgcolor'.
See the xcolor package documentation for explanation.
Type H <return> for immediate help.
...
! Emergency stop.
...
l.100 ...{rgb}{0.941, 0.941, 0.941}\color{fgcolor}
\begin{kframe}
! ==> Fatal error occurred, no output PDF file produced!
--- failed re-building ‘TMixClust.Rnw’
SUMMARY: processing the following file failed:
‘TMixClust.Rnw’
Error: Vignette re-building failed.
Execution halted
