quadrantGate            package:flowStats            R Documentation

_A_u_t_o_m_a_t_e_d _q_u_a_d _g_a_t_i_n_g

_D_e_s_c_r_i_p_t_i_o_n:

     This function tries to find the most likely separation of
     two-dimensional flow cytometry in four quadrants.

_U_s_a_g_e:

     quadrantGate(x, stains, alpha=c("min", "min"), sd=c(2, 2), plot=FALSE,
     filterId="defaultQuadGate", ...)

_A_r_g_u_m_e_n_t_s:

       x: A 'flowSet' or 'flowFrame'. 

  stains: A character vector of length two giving the two flow
          parameters for which the quad gate is to be computed. 

alpha, sd: Tuning factors to control the computation of the gate
          boundaries. See 'rangeGate' for details. 

    plot: Logical. Produce plots of intermediate results. 

filterId: Character, the name assigned to the resulting filter. 

     ...: Additional arguments 

_D_e_t_a_i_l_s:

     The most likely separation between postitive and negative stains
     for two-dimensional data is computed based on density estimates.
     Essentially, the gate parameters are first fitted separately for
     the two parameters and later combined. See the documentation for
     'rangeGate' for details. There is a certain amount of heuristics
     involved in this process. The algorithm can be slightly tweaked
     using the 'alpha' and 'sd' arguments. Their values will be
     recycled for the two dimensions unless explicitely given as
     vectors of length 2.

_V_a_l_u_e:

     An object of class 'quadGate'.

_A_u_t_h_o_r(_s):

     Florian Hahne

_S_e_e _A_l_s_o:

     'quadGate', 'rangeGate'

_E_x_a_m_p_l_e_s:

     data(GvHD)
     dat <- GvHD[pData(GvHD)$Patient==10]
     dat <- transform(dat, "FL4-H"=asinh(`FL4-H`), "FL2-H"=asinh(`FL2-H`))
     qg <- quadrantGate(dat, c("FL2-H", "FL4-H"))
     qg
     if(require(flowViz))
     xyplot(`FL2-H`~`FL4-H`, dat, filter=qg)
     qg <- quadrantGate(dat, c("FL2-H", "FL4-H"), alpha=c(0.1, 0.9), plot=TRUE)

