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39 lines
No EOL
1.1 KiB
R
39 lines
No EOL
1.1 KiB
R
cnts_casein <- cpm(y)[y$genes$Symbol == "Csn1s2b", ]
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cnts_rndm <- cpm(y)[100, ]
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df <- data.frame(Casein = cnts_casein,
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Random = cnts_rndm,
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targets[, c("CellType", "Status")])
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p <- ggplot(df, aes(x=Random, y=1,
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color=CellType, shape=Status)) +
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geom_point(size=2.5) +
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scale_x_log10() +
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scale_y_log10() +
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theme_classic() +
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theme(axis.title.y = element_blank(),
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axis.text.y = element_blank(),
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axis.ticks.y = element_blank(),
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axis.line.y = element_blank(),
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legend.position = "top",
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legend.box = "vertical",
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plot.margin = margin(0.5, 0.5, 0.5, 0.5, "cm"))
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ggsave("Random.png",
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p,
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width = 3,
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height = 3)
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p <- ggplot(df, aes(x=1, y=Random,
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color=CellType, shape=Status)) +
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geom_point(size=2.5) +
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scale_x_log10() +
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scale_y_log10() +
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theme(axis.title.x = element_blank(),
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axis.text.x = element_blank(),
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axis.ticks.x = element_blank())
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ggsave("Random.png",
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p)
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xlab(paste("PC1:", pc1_var, "% variance")) +
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ylab(paste("PC2:", pc2_var, "% variance")) |