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dynOmics-package           package:dynOmics            R Documentation

_F_a_s_t _F_o_u_r_i_e_r _t_r_a_n_s_f_o_r_m _t_o _e_s_t_i_m_a_t_e _d_e_l_a_y_s _i_n _e_x_p_r_e_s_s_i_o_n _i_n_i_t_i_a_t_i_o_n _t_o
_i_d_e_n_t_i_f_y _a_s_s_o_c_i_a_t_i_o_n_s _b_e_t_w_e_e_n _t_i_m_e _c_o_u_r_s_e '_o_m_i_c_s' _d_a_t_a.

_D_e_s_c_r_i_p_t_i_o_n:

     The package provides functions to identify associations within one
     or between two time course 'omics' data and visualise the
     associations : associateData to estimate the delays and identify
     associations of data sets containing time course 'omics'
     experiments; plot.associations: to visualise associated profiles.

_D_e_t_a_i_l_s:

       Package:   dynOmics   
       Type:      Package    
       Version:   1.2        
       Date:      2018-06-12 
       License:   GPL-2      
       LazyLoad:  yes        
      
     Functions for associating data: 'associateData'
     Functions for summarization: 'summary.associations'
     Functions for plots: 'plot.associations'

_A_u_t_h_o_r(_s):

     Jasmin Straube with contributions from Kim-Anh Le Cao, Emma Huang
     and Anne Bernard

     Maintainer: Jasmin Straube <j.straube@qimrberghofer.edu.au>


Metabolites              package:dynOmics              R Documentation

_M_e_t_a_b_o_l_i_t_e _a_n_d _T_r_a_n_s_c_r_i_p_t _S_i_m_u_l_a_t_i_o_n _D_a_t_a

_D_e_s_c_r_i_p_t_i_o_n:

     Simulated data were received from Redestig et al., 2011.
     Metabolite and transcript levels were obtained using an impulse
     model (Chechik and Koller, 2009). Functions were used to model
     five different metabolite patterns and for each metabolite 50
     associated transcript levels. Time lags were introduced in the
     range from -2 to 2 with the probability 0.1, 0.2, 0.4, 0.2, 0.1.
     Simulated profiles have seven time points and normal distributed
     noise was introduced with mean zero and standard deviation 0.1.

_U_s_a_g_e:

     data(Metabolites)
     
_F_o_r_m_a_t:

     This data set contains the simulated expression of 5 metabolites
     for 7 time points.

_D_e_t_a_i_l_s:

        • Metabolites. data matrix with 7 rows and 5 columns. Each row
          represents an experimental time sample, and each column a
          single metabolite.

_S_o_u_r_c_e:

     The Metabolite Simulation Data is based on the the paper of
     Redestig _et al._ (2011).

_R_e_f_e_r_e_n_c_e_s:

     Redestig,H. and Costa,I.G. Detection and interpretation of
     metabolite-transcript coresponses using combined profiling data.
     _Bioinformatics_ *27*(13) (2011), pp. i357 65.


Transcripts              package:dynOmics              R Documentation

_T_r_a_n_s_c_r_i_p_t _S_i_m_u_l_a_t_i_o_n _D_a_t_a

_D_e_s_c_r_i_p_t_i_o_n:

     Simulated data were received from Redestig et al., 2011.
     Metabolite and transcript levels were obtained using an impulse
     model (Chechik and Koller, 2009). Functions were used to model
     five different metabolite patterns and for each metabolite 50
     associated transcript levels. Time lags were introduced in the
     range from -2 to 2 with the probability 0.1, 0.2, 0.4, 0.2, 0.1.
     Simulated profiles have seven time points and normal distributed
     noise was introduced with mean zero and standard deviation 0.1.

_U_s_a_g_e:

     data(Transcripts)
     
_F_o_r_m_a_t:

     This data set contains the simulated expression 250 transcripts
     for 7 time points.

_D_e_t_a_i_l_s:

        • Transcripts. data matrix with 7 rows and 250 columns. Each
          row represents an experimental time sample, and each column a
          single transcript.

_S_o_u_r_c_e:

     The Transcript Simulation Data is based on the the paper of
     Redestig _et al._ (2011).

_R_e_f_e_r_e_n_c_e_s:

     Redestig,H. and Costa,I.G. Detection and interpretation of
     metabolite-transcript coresponses using combined profiling data.
     _Bioinformatics_ *27*(13) (2011), pp. i357 65.


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