R/plotting_rna.R

In shahcompbio/signals: Single Cell Genomes with Allele Specificity

#' @export
per_chr_baf_plot <- function(haps, filtern = 9, perarm = FALSE, labelclones = FALSE) {
  if (labelclones) {
    if (perarm) {
      chridx <- data.frame(chrarm = paste0(rep(c(paste0(seq(1:22)), "X", "Y"), each = 2), rep(c("p", "q"), 24))) %>%
        dplyr::mutate(idx = 1:dplyr::n())

      hst <- haps %>%
        dplyr::filter(total > filtern) %>%
        dplyr::left_join(chridx, by = c("chrarm")) %>%
        dplyr::mutate(chrarmf = forcats::fct_reorder(as.factor(paste0("Chr ", chrarm)), idx)) %>%
        ggplot2::ggplot(ggplot2::aes(x = BAF, fill = clone_id)) +
        ggplot2::geom_histogram(bins = 30, alpha = 0.5) +
        ggplot2::facet_wrap(~chrarmf, scales = "free_y") +
        cowplot::theme_cowplot() +
        ggplot2::scale_x_continuous(breaks = c(0.0, 0.5, 1.0), limits = c(-0.05, 1.05)) +
        cowplot::panel_border() +
        ggplot2::geom_vline(xintercept = 0.5, lty = 2, size = 0.5, col = "firebrick4") +
        ggplot2::theme(
          axis.title.y = ggplot2::element_blank(),
          axis.text.y = ggplot2::element_blank(),
          axis.ticks.y = ggplot2::element_blank()
        )
    } else {
      chridx <- data.frame(chr = c(paste0(1:22), "X", "Y"), idx = seq(1:24))

      hst <- haps %>%
        dplyr::filter(total > filtern) %>%
        dplyr::mutate(chrf = forcats::fct_reorder(as.factor(paste0("Chr ", chr)), idx)) %>%
        ggplot2::ggplot(ggplot2::aes(x = BAF, fill = clone_id)) +
        ggplot2::geom_histogram(bins = 30, alpha = 0.5) +
        ggplot2::facet_wrap(~chrf, scales = "free_y") +
        cowplot::theme_cowplot() +
        ggplot2::scale_x_continuous(breaks = c(0.0, 0.5, 1.0), limits = c(-0.05, 1.05)) +
        cowplot::panel_border() +
        ggplot2::geom_vline(xintercept = 0.5, lty = 2, size = 0.5, col = "firebrick4") +
        ggplot2::theme(
          axis.title.y = ggplot2::element_blank(),
          axis.text.y = ggplot2::element_blank(),
          axis.ticks.y = ggplot2::element_blank()
        )
    }
  }
  else {
    if (perarm) {
      chridx <- data.frame(chrarm = paste0(rep(c(paste0(seq(1:22)), "X", "Y"), each = 2), rep(c("p", "q"), 24))) %>%
        dplyr::mutate(idx = 1:dplyr::n())

      hst <- haps %>%
        dplyr::mutate(arm = coord_to_arm(chr, start)) %>%
        dplyr::mutate(chrarm = paste0(chr, arm)) %>%
        dplyr::group_by(chr, arm, chrarm, cell_id) %>%
        dplyr::summarise(
          alleleA = sum(alleleA, na.rm = TRUE),
          alleleB = sum(alleleB, na.rm = TRUE)
        ) %>%
        dplyr::ungroup() %>%
        dplyr::mutate(
          BAF = alleleB / (alleleA + alleleB),
          total = alleleB + alleleA
        ) %>%
        dplyr::filter(total > filtern) %>%
        dplyr::left_join(chridx, by = c("chrarm")) %>%
        dplyr::mutate(chrarmf = forcats::fct_reorder(as.factor(paste0("Chr ", chrarm)), idx)) %>%
        ggplot2::ggplot(ggplot2::aes(x = BAF)) +
        ggplot2::geom_histogram(bins = 30, alpha = 0.5) +
        ggplot2::facet_wrap(~chrarmf, scales = "free_y") +
        cowplot::theme_cowplot() +
        ggplot2::scale_x_continuous(breaks = c(0.0, 0.5, 1.0), limits = c(-0.05, 1.05)) +
        cowplot::panel_border() +
        ggplot2::geom_vline(xintercept = 0.5, lty = 2, size = 0.5, col = "firebrick4") +
        ggplot2::theme(
          axis.title.y = ggplot2::element_blank(),
          axis.text.y = ggplot2::element_blank(),
          axis.ticks.y = ggplot2::element_blank()
        )
    } else {
      chridx <- data.frame(chr = c(paste0(1:22), "X", "Y"), idx = seq(1:24))

      hst <- haps %>%
        dplyr::group_by(chr, cell_id) %>%
        dplyr::summarise(
          alleleA = sum(alleleA, na.rm = TRUE),
          alleleB = sum(alleleB, na.rm = TRUE)
        ) %>%
        dplyr::ungroup() %>%
        dplyr::mutate(
          BAF = alleleB / (alleleA + alleleB),
          total = alleleB + alleleA
        ) %>%
        dplyr::filter(total > filtern) %>%
        dplyr::left_join(chridx, by = "chr") %>%
        dplyr::mutate(chrf = forcats::fct_reorder(as.factor(paste0("Chr ", chr)), idx)) %>%
        ggplot2::ggplot(ggplot2::aes(x = BAF)) +
        ggplot2::geom_histogram(bins = 30, alpha = 0.5) +
        ggplot2::facet_wrap(~chrf, scales = "free_y") +
        cowplot::theme_cowplot() +
        ggplot2::scale_x_continuous(breaks = c(0.0, 0.5, 1.0), limits = c(-0.05, 1.05)) +
        cowplot::panel_border() +
        ggplot2::geom_vline(xintercept = 0.5, lty = 2, size = 0.5, col = "firebrick4") +
        ggplot2::theme(
          axis.title.y = ggplot2::element_blank(),
          axis.text.y = ggplot2::element_blank(),
          axis.ticks.y = ggplot2::element_blank()
        )
    }
  }

  return(hst)
}

#' @export
per_segment_baf_plot <- function(hscn, filtern = 9, labelclones = FALSE) {
  
  if (is.hscnrna(hscn)) {
    cndat <- hscn$hscn
  } else {
    cndat <- hscn
  }
  
  mixedrank = function(x) order(gtools::mixedorder(x))
  
  if (labelclones) {
      
      chridx <- dplyr::distinct(cndat, chr, segid) %>%
        dplyr::arrange(mixedrank(segid)) %>% 
        dplyr::mutate(idx = 1:dplyr::n())
      
      hst <- cndat %>%
        dplyr::filter(total > filtern) %>%
        dplyr::left_join(chridx) %>% 
        dplyr::mutate(segidf = stringr::str_replace_all(segid, "_", "\n")) %>% 
        dplyr::mutate(segidf = forcats::fct_reorder(as.factor(segidf), idx)) %>%
        ggplot2::ggplot(ggplot2::aes(x = BAF, fill = clone_id)) +
        ggplot2::geom_histogram(bins = 30, alpha = 0.5) +
        ggplot2::facet_wrap(~segidf, scales = "free_y") +
        cowplot::theme_cowplot(font_size = 8) +
        ggplot2::scale_x_continuous(breaks = c(0.0, 0.5, 1.0), limits = c(-0.05, 1.05)) +
        cowplot::panel_border() +
        ggplot2::geom_vline(xintercept = 0.5, lty = 2, size = 0.5, col = "firebrick4") +
        ggplot2::theme(
          axis.title.y = ggplot2::element_blank(),
          axis.text.y = ggplot2::element_blank(),
          axis.ticks.y = ggplot2::element_blank()
        )
  } else {
    hst <- cndat %>%
      dplyr::filter(total > filtern) %>%
      dplyr::left_join(chridx) %>% 
      dplyr::mutate(segidf = stringr::str_replace_all(segid, "_", "\n")) %>% 
      dplyr::mutate(segidf = forcats::fct_reorder(as.factor(segidf), idx)) %>%
      ggplot2::ggplot(ggplot2::aes(x = BAF)) +
      ggplot2::geom_histogram(bins = 30, alpha = 0.5) +
      ggplot2::facet_wrap(~segidf, scales = "free_y") +
      cowplot::theme_cowplot(font_size = 8) +
      ggplot2::scale_x_continuous(breaks = c(0.0, 0.5, 1.0), limits = c(-0.05, 1.05)) +
      cowplot::panel_border() +
      ggplot2::geom_vline(xintercept = 0.5, lty = 2, size = 0.5, col = "firebrick4") +
      ggplot2::theme(
        axis.title.y = ggplot2::element_blank(),
        axis.text.y = ggplot2::element_blank(),
        axis.ticks.y = ggplot2::element_blank()
      )
  }
  
  return(hst)
}


#' @export
plot_proportions <- function(hscn_dna_arm, hscn_rna_arm, perarm = FALSE) {
  prop_rna <- hscn_rna_arm %>%
    dplyr::mutate(state_AS_phased = ifelse(state > 5, "Other", state_AS_phased)) %>%
    dplyr::group_by(chr, chrarm, state_AS_phased) %>%
    dplyr::summarise(n = dplyr::n()) %>%
    dplyr::mutate(f = n / sum(n)) %>%
    dplyr::mutate(assay = "RNA")

  prop_dna <- hscn_dna_arm %>%
    dplyr::mutate(state_AS_phased = ifelse(state > 5, "Other", state_AS_phased)) %>%
    dplyr::group_by(chr, chrarm, state_AS_phased) %>%
    dplyr::summarise(n = dplyr::n()) %>%
    dplyr::mutate(f = n / sum(n)) %>%
    dplyr::mutate(assay = "DNA")

  prop <- dplyr::bind_rows(prop_rna, prop_dna) %>%
    dplyr::mutate(ord = ifelse(assay == "DNA", 1, 0)) %>%
    dplyr::mutate(chrord = ifelse(chr == "X", 24, as.numeric(as.character(chr))))

  barplot <- prop %>%
    dplyr::ungroup() %>%
    dplyr::mutate(chrarm = forcats::fct_reorder(chrarm, chrord)) %>%
    ggplot2::ggplot(ggplot2::aes(
      x = assay,
      y = f,
      fill = state_AS_phased,
      alpha = forcats::fct_reorder(assay, ord)
    )) +
    ggplot2::geom_bar(stat = "identity") +
    ggplot2::facet_wrap(~chrarm, nrow = 1) +
    cowplot::theme_cowplot() +
    ggplot2::theme(
      panel.spacing = grid::unit(0.1, "lines"),
      legend.position = "bottom",
      legend.title = ggplot2::element_blank()
    ) +
    ggplot2::guides(
      fill = ggplot2::guide_legend(nrow = 3),
      alpha = ggplot2::guide_legend(nrow = 2)
    ) +
    ggplot2::xlab("") +
    ggplot2::ylab("Proportion") +
    ggplot2::scale_alpha_discrete(range = c(0.65, 1.0)) +
    ggplot2::theme(
      axis.title.x = ggplot2::element_blank(),
      axis.text.x = ggplot2::element_blank(),
      axis.ticks.x = ggplot2::element_blank(),
      axis.line.x = ggplot2::element_blank()
    ) +
    ggplot2::scale_y_continuous(expand = c(0, 0))

  return(barplot)
}