detectSB            package:MANOR            R Documentation(latin1)

_S_p_a_t_i_a_l _b_i_a_s _d_e_t_e_c_t_i_o_n

_D_e_s_c_r_i_p_t_i_o_n:

     This function detects spatial bias on array CGH.

_U_s_a_g_e:

     ## S3 method for class 'arrayCGH':
     detectSB(arrayCGH, variable, proportionup=0.25,
     proportiondown,type="up", thresholdup=0.2, thresholddown=0.2, ... ) 

_A_r_g_u_m_e_n_t_s:

arrayCGH: Object of 'arrayCGH'.

variable: Variable used to compare the mean of zones detected by 'nem'

proportionup: Maximal proportion of the array which may be affected by
          spatial bias with high values.

proportiondown: Maximal proportion of the array which may be affected
          by spatial bias with low values.

    type: Type of spatial bias detected. Specify either "up" (to detect
          spatial bias with high values), or "down" (to detect spatial
          bias with low values) or "upanddown" (to detect both type of
          spatial bias).

thresholdup: Threshold used to detect spatial bias with high values.

thresholddown: Threshold used to detect spatial bias with low values.

     ...: 

_D_e_t_a_i_l_s:

     You must run the 'arrayTrend' and 'nem' function before detecting
     spatial bias: the 'arrayTrend' computes a spatial trend and the
     'nem' function performs a classification with spatial constraints
     defining different zones on the array. Based on those results,
     spatial bias is detected.

_V_a_l_u_e:

     An object of class 'arrayCGH' with the following added information
     in the data.frame attribute 'arrayValues': 

      SB: Spots located in zone of spatial bias are coded either by 1
          (if they correspond to a spatial bias with high values) or by
          -1 (if they correspond to a spatial bias with low values).
          Otherwise they are coded by 0.

_N_o_t_e:

     People interested in tools for array-CGH analysis can visit our
     web-page: <URL: http://bioinfo.curie.fr>.

_A_u_t_h_o_r(_s):

     Philippe Hup, Philippe.Hupe@.curie.fr.

_R_e_f_e_r_e_n_c_e_s:

     P. Neuvial, P. Hup, I. Brito, S. Liva, E. Mani, C. Brennetot, A.
     Aurias, F. Radvanyi, and E. Barillot. _Spatial normalization of
     array-CGH data_. BMC Bioinformatics, 7(1):264. May 2006.

_S_e_e _A_l_s_o:

     'arrayTrend', 'nem'

_E_x_a_m_p_l_e_s:

     data(spatial)  ## arrays with local spatial effects

     ## Plot of LogRatio measured on the array CGH
     arrayPlot(edge,"LogRatio", main="Log2-Ratio measured on the array
     CGH", zlim=c(-1,1), bar="v", mediancenter=TRUE) 

     ## Spatial trend of the scaled log-ratios (the variable "ScaledLogRatio"
     ## equals to the log-ratio minus the median value of the corresponding
     ## chromosome arm)

     edgeTrend <- arrayTrend(edge, variable="ScaledLogRatio",
     span=0.03, degree=1, iterations=3, family="symmetric")   
     arrayPlot(edgeTrend, variable="Trend", main="Spatial trend of the
     array CGH", bar="v")  

     ## Not run: 
     ## Classification with spatial constraint of the spatial trend
     edgeNem <- nem(edgeTrend, variable="Trend")
     arrayPlot(edgeNem, variable="ZoneNem", main="Spatial zones identified
     by nem", bar="v") 

     # Detection of spatial bias
     edgeDet <- detectSB(edgeNem, variable="LogRatio", proportionup=0.25,type="up", thresholdup=0.15) 
     arrayPlot(edgeDet, variable="SB", main="Zone of spatial bias in red", bar="v")

     # CGH profile 
     plot(LogRatio ~ PosOrder, data=edgeDet$arrayValues,
     col=c("black","red")[as.factor(SB)], pch=20, main="CGH profile: spots
     located in spatial bias are in red")  
     ## End(Not run)

