FastQC, Trimming, Overall QC (initial)

rnaseq/step6_overall_QC/03 - Sample Counts.R

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+# Total counts per sample
+# Normalized with limma::voom
+
+source("__ - Preloader.R", verbose=T)
+
+
+# The analysis
+norm.expr.data <- expression.data %>%
+	tibble::column_to_rownames("Gene")
+norm.expr.data <- norm.expr.data[rowSums(norm.expr.data) >= 10,] %>%
+	limma::voom() %>%
+	as.matrix()
+
+# Total counts per sample
+total.count.per.sample <- expression.data %>%
+	tibble::column_to_rownames("Gene") %>%
+	colSums()
+
+data.frame(
+		sample = names(total.count.per.sample),
+		counts = as.numeric(total.count.per.sample)
+	) %>%
+	readr::write_csv(file.path(results.dir, "total.counts.per.sample.csv"))
+
+
+norm.data <- norm.expr.data %>%
+  as.data.frame() %>%
+  tibble::rownames_to_column(
+    "Gene"
+  ) %>%
+  tidyr::gather(
+    key = "sample.id",
+    value = "expr.value",
+    -Gene
+  ) %>%
+  dplyr::left_join(
+    y = master.Table %>%
+      dplyr::filter(
+          !is.na(GenomeScan_ID)
+      ) %>%
+      dplyr::mutate(
+          id = dplyr::case_when(
+            stringr::str_trim(gender) == "" ~ paste0("Water ", dplyr::row_number()),
+            TRUE ~ sample.id
+          ),
+          gender = dplyr::case_when(
+            stringr::str_trim(gender) == "" ~ "water",
+            !is.na(gender) ~ as.character(gender)
+          )
+      ) %>%
+      dplyr::select(
+        GenomeScan_ID,
+        gender,
+        id
+      ),
+    by = c("sample.id" = "GenomeScan_ID")
+  )
+
+norm.plot <- norm.data %>%
+  ggplot2::ggplot(
+    mapping = ggplot2::aes(
+      x = id,
+      y = expr.value,
+      fill = gender
+    )
+  ) +
+  ggplot2::geom_boxplot() +
+  ggplot2::scale_fill_manual(
+    values = c(
+      "male" = "blue",
+      "female" = "red",
+      "water" = "green"
+    )
+  ) +
+  ggplot2::labs(
+    title = "Normalized expression values distribution",
+    y = "Normalized expression values (limma::voom)",
+    x = "Sample",
+    gender = "Gender"
+  ) +
+  ggprism::theme_prism() +
+  ggplot2::theme(
+    axis.text.x = ggplot2::element_text(angle = 90)
+  )
+
+ggplot2::ggsave(
+  filename = file.path(results.dir, "counts.per.sample.normalised.png"),
+  plot = norm.plot,
+  width = 40,
+  height = 20,
+  units = "cm"
+)
+
+
+
+expr.data <- expression.data %>%
+  tidyr::gather(
+    key = "sample.id",
+    value = "expr.value",
+    -Gene
+  ) %>%
+  dplyr::filter(
+    expr.value != 0
+  ) %>%
+  dplyr::left_join(
+    y = master.Table %>%
+      dplyr::filter(
+          !is.na(GenomeScan_ID)
+      ) %>%
+      dplyr::mutate(
+          id = dplyr::case_when(
+            stringr::str_trim(gender) == "" ~ paste0("Water ", dplyr::row_number()),
+            TRUE ~ sample.id
+          ),
+          gender = dplyr::case_when(
+            stringr::str_trim(gender) == "" ~ "water",
+            !is.na(gender) ~ as.character(gender)
+          )
+      ) %>%
+      dplyr::select(
+        GenomeScan_ID,
+        gender,
+        id
+      ),
+    by = c("sample.id" = "GenomeScan_ID")
+  )
+
+expr.plot <- expr.data %>%
+  ggplot2::ggplot(
+    mapping = ggplot2::aes(
+      x = id,
+      y = expr.value,
+      fill = gender
+    )
+  ) +
+  ggplot2::geom_boxplot() +
+  ggplot2::scale_fill_manual(
+    values = c(
+      "male" = "blue",
+      "female" = "red",
+      "water" = "green"
+    )
+  ) +
+  ggplot2::scale_y_continuous(trans='log2')  +
+  ggplot2::labs(
+    title = "Raw expression values distribution, without zero's",
+    y = "Expression values",
+    x = "Sample",
+    gender = "Gender"
+  ) +
+  ggprism::theme_prism() +
+  ggplot2::theme(
+    axis.text.x = ggplot2::element_text(angle = 90)
+  )
+
+ggplot2::ggsave(
+  filename = file.path(results.dir, "counts.per.sample.raw.zeros.removed.png"),
+  plot = expr.plot,
+  width = 40,
+  height = 20,
+  units = "cm"
+)
+