isPeak                package:PROcess                R Documentation

_L_o_c_a_t_e _P_e_a_k_s _i_n _a _S_p_e_c_t_r_u_m

_D_e_s_c_r_i_p_t_i_o_n:

     Find local maxima of a spectrum.

_U_s_a_g_e:

     isPeak(f,SoN = 2,span = 81,sm.span=11,plot=FALSE,add = FALSE,
     zerothrsh=2,area.w = 0.003, ratio = 0.2, ...) 

_A_r_g_u_m_e_n_t_s:

       f: a matrix of two columns representing a spectrum, with the 
          first column the m/z value and second the intensity

     SoN: signal to noise ratio criterion for peak detection

    span: parameter for estimating local variance before  peak
          detection; default is 81 points, that is, 40  points to the
          left and right of a point of which the  variance is being
          estimated.

 sm.span: parameter for smoothing the spectrum before  peak detection;
          default is 11 points, that is, 5  points to the left and
          right of a point being smoothed

    plot: logical, plot the smoothed spectrum and peaks? 

     add: add to the existing raw and baseline-substracted plot?

zerothrsh: ignore peaks whose intensity values are below zerothrsh.

  area.w: the neighbourhood of a peak m/z, mz*(1-area.w, 1+area.w).

   ratio: if area/max(area) > ratio, the peak is retained.

     ...: further arguments that get passed on to 'plot'.

_D_e_t_a_i_l_s:

     A spectrum is smoothed first using the nearest `span'  neighbours.
     A larger span `sm.span' is needed to estimate the local variation
     so that it is not overestimated due to the peaks nearby.  Then
     potential peaks are identified using  Ripley's `peaks' function
     with `span' points.

     Peaks that satify the conditions that the (smoothed) signal  to
     noise ratio is greater than `SoN' and that the smoothed  signal is
     greater than 1.64 * mad(sm) are returned.

_V_a_l_u_e:

     A data frame with five components, `peak',`smooth',`mz' and
     `sigmas', each of length the number of rows in `f'.  `peak' is
     logical indicating whethere there is a peak or not  (Y/N),
     `smooth' the smooth of the spectrum, `mz' the same as  `f[,1]',
     `sigmas' the estimates of local variation and `area' the area
     associated with each peak after the first pass.

_A_u_t_h_o_r(_s):

     Xiaochun Li

_E_x_a_m_p_l_e_s:

     example(bslnoff)
     pkobj <- isPeak(bseoff,span=81,sm.span=11,plot=TRUE)

