Help for PCA analysis

Question

[axe880]

Hi everyone,

I am looking to generate some PCA plots for my current project. I am aiming to generate four different plots. This represents the two plant varieties I am using (drought tolerant and drought susceptible) as well as the two tissue types (leaf and root).

I am working with an example script that was provided to me. My issue is that I am unable to successfully edit this script. I am looking to plot all four replicate types (described by the "Time" category for each of the four listed categories above.

Any help would be appreciated.

Here is the script:

# remove genes with low expression
keep <- rowSums(counts(dds)) >= 10
dds <- dds[keep,]

# transform data before saving output for use later
vsd <- vst(dds, blind = TRUE)

# save
write.csv(as.data.frame(assay(vsd)) %>% rownames_to_column(var = "gene"),
          here("VSDtransformed"),
          row.names = FALSE)

# PCA
pca_data <- plotPCA(vsd, intgroup = c("Tissue", "Time", "Variety"), ntop = 1000, returnData = TRUE)

# Variance Explained
var_capture <- round(100 * attr(pca_data, "percentVar"), 1)

# Plot
p1 <- plot_ly(pca_data, x = ~PC1, y = ~PC2, text = ~paste("Sample:", name, "<br>Variety:", Variety),
              mode = "markers", color = ~Time, symbol = ~Tissue, width = 900)
p1 %>% layout(xaxis =list(title = paste0("PC1", var_capture[1], "% variance")),
              yaxis = list(title = paste0("PC2", var_capture[2], "% variance")))

[iraun]

In order to make your post more clean, I suggest you using the format "Code Sample" to format your code lines in a better way. Also, for having better answers, it is usually a good idea to provide some example of the input data, and also, the specific error you are getting when running the code :).

Answer 1

[swbarnes2]

I'm not sure why you don't want to put all your samples into one plot, but if you really don't want to do that, here's how you can make a smaller dds object at is a subset of yours. Something like:

dds_drop <- dds[ ,dds$Day == "Day0"]

Then make a vsd for that object, and recalculate PCAData for it.

[axe880]

Thank you. I essentially have 48 samples:

12 for Tolerant (Root) 12 for Tolerant (Leaf) 12 for Susceptible (Root) 12 for Susceptible (Leaf)

Each 12 represents four time points with three replicates each. I am aiming to separate the dataset into these four groups so I can check the replicates are closely grouped for each time point.

Thanks again