Mercurial > repos > eschen42 > w4mclassfilter

comparison w4mclassfilter_wrapper.R @ 13:b24ca78a425b draft

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planemo upload for repository https://github.com/HegemanLab/w4mclassfilter_galaxy_wrapper/tree/master commit 32cf96ed6c39a93eb9c6cf00494b128bd3c3febe
author eschen42
date Mon, 03 Sep 2018 22:28:03 -0400
parents 518cc205f289
children
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12:518cc205f289 13:b24ca78a425b
100 ## ----------------------------- 100 ## -----------------------------
101 ## Transformation and imputation 101 ## Transformation and imputation
102 ## ----------------------------- 102 ## -----------------------------
103 my_w4m_filter_imputation <- if (transformation == "log10") { 103 my_w4m_filter_imputation <- if (transformation == "log10") {
104 function(m) { 104 function(m) {
105 if (!is.matrix(m))
106 stop("Cannot impute and transform data - the supplied data is not in matrix form")
107 if (nrow(m) == 0)
108 stop("Cannot impute and transform data - data matrix has no rows")
109 if (ncol(m) == 0)
110 stop("Cannot impute and transform data - data matrix has no columns")
105 suppressWarnings( 111 suppressWarnings(
106 # suppress warnings here since non-positive values will produce NaN's that will be fixed in the next step 112 # suppress warnings here since non-positive values will produce NaN's that will be fixed in the next step
107 m <- log10(m) 113 m <- log10(m)
108 ) 114 )
109 # replace NaN values with zero 115 return ( w4m_filter_imputation(m) )
110 m[is.nan(m)] <- 0 116 }
111 # replace NA values with zero 117 } else if (transformation == "log2") {
112 m[is.na(m)] <- 0 118 function(m) {
113 # replace negative values with zero, if applicable (It should never be applicable!) 119 if (!is.matrix(m))
114 m[m<0] <- 0 120 stop("Cannot impute and transform data - the supplied data is not in matrix form")
115 # return matrix as the result 121 if (nrow(m) == 0)
116 return (m) 122 stop("Cannot impute and transform data - data matrix has no rows")
123 if (ncol(m) == 0)
124 stop("Cannot impute and transform data - data matrix has no columns")
125 suppressWarnings(
126 # suppress warnings here since non-positive values will produce NaN's that will be fixed in the next step
127 m <- log2(m)
128 )
129 return ( w4m_filter_imputation(m) )
117 } 130 }
118 } else { 131 } else {
119 # use the method from the w4mclassfilter class 132 # use the method from the w4mclassfilter class
120 w4m_filter_imputation 133 w4m_filter_imputation
121 } 134 }