Mercurial > repos > davidvanzessen > test_plotting_merged

comparison RScript.r @ 5:021d293121bb draft

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author davidvanzessen
date Mon, 14 Oct 2013 09:49:29 -0400
parents 10cfa5e9186e
children f9a657db7af5
comparison
equal deleted inserted replaced
4:10cfa5e9186e 5:021d293121bb
106 pJ 106 pJ
107 dev.off(); 107 dev.off();
108 108
109 109
110 plotVD <- function(dat){ 110 plotVD <- function(dat){
111 #dat = dat[order(dat[,8],dat[,9]),]
111 img = ggplot() + 112 img = ggplot() +
112 geom_tile(data=dat, aes(x=factor(Top.D.Gene), y=factor(Top.V.Gene), fill=log)) + 113 geom_tile(data=dat, aes(x=factor(reorder(Top.D.Gene, chr.orderD)), y=factor(reorder(Top.V.Gene, chr.orderV)), fill=log)) +
113 theme(axis.text.x = element_text(angle = 90, hjust = 1)) + 114 theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
114 scale_fill_gradient(low="gold", high="blue", na.value="white") + 115 scale_fill_gradient(low="gold", high="blue", na.value="white") +
115 ggtitle(unique(dat$Sample)) + 116 ggtitle(unique(dat$Sample)) +
116 xlab("D genes") + 117 xlab("D genes") +
117 ylab("V Genes") 118 ylab("V Genes")
126 cartegianProductVD = expand.grid(Top.V.Gene = Vchain$v.name, Top.D.Gene = Dchain$v.name, Sample = unique(test$Sample)) 127 cartegianProductVD = expand.grid(Top.V.Gene = Vchain$v.name, Top.D.Gene = Dchain$v.name, Sample = unique(test$Sample))
127 128
128 completeVD = merge(VandDCount, cartegianProductVD, all.y=TRUE) 129 completeVD = merge(VandDCount, cartegianProductVD, all.y=TRUE)
129 completeVD$Length = as.numeric(completeVD$Length) 130 completeVD$Length = as.numeric(completeVD$Length)
130 completeVD$log = log(completeVD$Length) 131 completeVD$log = log(completeVD$Length)
132 completeVD = merge(completeVD, Vchain, by.x="Top.V.Gene", by.y="v.name", all.x=TRUE)
133 completeVD = merge(completeVD, Dchain, by.x="Top.D.Gene", by.y="v.name", all.x=TRUE)
131 #completeVD$log[is.na(completeVD$log)] = 0 134 #completeVD$log[is.na(completeVD$log)] = 0
132 l = split(completeVD, f=completeVD[,"Sample"]) 135 l = split(completeVD, f=completeVD[,"Sample"])
133 136
134 lapply(l, FUN=plotVD) 137 lapply(l, FUN=plotVD)
135 138
136 139
137 140
138 plotVJ <- function(dat){ 141 plotVJ <- function(dat){
142 #dat = dat[order(dat[,8],dat[,9]),]
139 img = ggplot() + 143 img = ggplot() +
140 geom_tile(data=dat, aes(x=factor(Top.J.Gene), y=factor(Top.V.Gene), fill=log)) + 144 geom_tile(data=dat, aes(x=factor(reorder(Top.J.Gene, chr.orderJ)), y=factor(reorder(Top.V.Gene, chr.orderV)), fill=log)) +
141 theme(axis.text.x = element_text(angle = 90, hjust = 1)) + 145 theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
142 scale_fill_gradient(low="gold", high="blue", na.value="white") + 146 scale_fill_gradient(low="gold", high="blue", na.value="white") +
143 ggtitle(unique(dat$Sample)) + 147 ggtitle(unique(dat$Sample)) +
144 xlab("J genes") + 148 xlab("J genes") +
145 ylab("V Genes") 149 ylab("V Genes")
153 cartegianProductVJ = expand.grid(Top.V.Gene = Vchain$v.name, Top.J.Gene = Jchain$v.name, Sample = unique(test$Sample)) 157 cartegianProductVJ = expand.grid(Top.V.Gene = Vchain$v.name, Top.J.Gene = Jchain$v.name, Sample = unique(test$Sample))
154 158
155 completeVJ = merge(VandJCount, cartegianProductVJ, all.y=TRUE) 159 completeVJ = merge(VandJCount, cartegianProductVJ, all.y=TRUE)
156 completeVJ$Length = as.numeric(completeVJ$Length) 160 completeVJ$Length = as.numeric(completeVJ$Length)
157 completeVJ$log = log(completeVJ$Length) 161 completeVJ$log = log(completeVJ$Length)
162 completeVJ = merge(completeVJ, Vchain, by.x="Top.V.Gene", by.y="v.name", all.x=TRUE)
163 completeVJ = merge(completeVJ, Jchain, by.x="Top.J.Gene", by.y="v.name", all.x=TRUE)
158 #completeVJ$log[is.na(completeVJ$log)] = 0 164 #completeVJ$log[is.na(completeVJ$log)] = 0
159 l = split(completeVJ, f=completeVJ[,"Sample"]) 165 l = split(completeVJ, f=completeVJ[,"Sample"])
160 lapply(l, FUN=plotVJ) 166 lapply(l, FUN=plotVJ)
161 167
162 plotDJ <- function(dat){ 168 plotDJ <- function(dat){
169 #dat = dat[order(dat[,8],dat[,9]),]
163 img = ggplot() + 170 img = ggplot() +
164 geom_tile(data=dat, aes(x=factor(Top.J.Gene), y=factor(Top.D.Gene), fill=log)) + 171 geom_tile(data=dat, aes(x=factor(reorder(Top.J.Gene, chr.orderJ)), y=factor(reorder(Top.D.Gene, chr.orderD)), fill=log)) +
165 theme(axis.text.x = element_text(angle = 90, hjust = 1)) + 172 theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
166 scale_fill_gradient(low="gold", high="blue", na.value="white") + 173 scale_fill_gradient(low="gold", high="blue", na.value="white") +
167 ggtitle(unique(dat$Sample)) + 174 ggtitle(unique(dat$Sample)) +
168 xlab("J genes") + 175 xlab("J genes") +
169 ylab("D Genes") 176 ylab("D Genes")
177 cartegianProductDJ = expand.grid(Top.D.Gene = Dchain$v.name, Top.J.Gene = Jchain$v.name, Sample = unique(test$Sample)) 184 cartegianProductDJ = expand.grid(Top.D.Gene = Dchain$v.name, Top.J.Gene = Jchain$v.name, Sample = unique(test$Sample))
178 185
179 completeDJ = merge(DandJCount, cartegianProductDJ, all.y=TRUE) 186 completeDJ = merge(DandJCount, cartegianProductDJ, all.y=TRUE)
180 completeDJ$Length = as.numeric(completeDJ$Length) 187 completeDJ$Length = as.numeric(completeDJ$Length)
181 completeDJ$log = log(completeDJ$Length) 188 completeDJ$log = log(completeDJ$Length)
189 completeDJ = merge(completeDJ, Dchain, by.x="Top.D.Gene", by.y="v.name", all.x=TRUE)
190 completeDJ = merge(completeDJ, Jchain, by.x="Top.J.Gene", by.y="v.name", all.x=TRUE)
182 #completeDJ$log[is.na(completeDJ$log)] = 0 191 #completeDJ$log[is.na(completeDJ$log)] = 0
183 l = split(completeDJ, f=completeDJ[,"Sample"]) 192 l = split(completeDJ, f=completeDJ[,"Sample"])
184 lapply(l, FUN=plotDJ) 193 lapply(l, FUN=plotDJ)
185 194
186 195