Package 'dotsViolin'

Makes a composite dot-plot and violin-plot

Description

This function makes a dot-plot and violin-plot

Usage

dots_and_violin(
  dataframe,
  colgroup,
  collabel,
  maxcountcol,
  widthdots,
  maxx,
  labelx,
  desiredorder,
  binwidth,
  adjust,
  binexp,
  fill_group = "fill_group",
  dots = TRUE,
  violin = TRUE
)

Arguments

dataframe	dataframe
colgroup	chr column to group by
collabel	label to be used in the plot
maxcountcol	numeric variable
widthdots	dotsize parameter for geom_dotplot
maxx	x axis maximum value
labelx	label for x axis
desiredorder	order for the colgroup categories
binwidth	see, plot_dotviolin
adjust	adjust param, see geom_violin
binexp	digit to modify size of bins with base 10
fill_group	2nd categorical data (use only 2 categories)
dots	boolean include dot plot
violin	boolean include violin plot

Value

A grid of ggplots that mimics a single plot

Examples

fabaceae_mode_counts <- get_modes_counts(fabaceae_clade_n_df, "clade", "parsed_n")
fabaceae_clade_n_df_count <- make_legend_with_stats(fabaceae_mode_counts, "label_count", 1, TRUE)
fabaceae_clade_n_df$label_count <- fabaceae_clade_n_df_count$label_count[match(
  fabaceae_clade_n_df$clade,
  fabaceae_clade_n_df_count$clade
)]
desiredorder1 <- unique(fabaceae_clade_n_df$clade)

dots_and_violin(
  fabaceae_clade_n_df, "clade", "label_count", "parsed_n", 2,
  30, "Chromosome haploid number", desiredorder1, 1, .85, 4,
  "ownwork",
  violin = FALSE
)

dots_and_violin(
  fabaceae_clade_n_df, "clade", "label_count", "parsed_n", 2,
  30, "Chromosome haploid number", desiredorder1, 1, .85, 4,
  dots = FALSE
)
dots_and_violin(
  fabaceae_clade_n_df, "clade", "label_count", "parsed_n", 2,
  30, "Chromosome haploid number", desiredorder1, 1, .85, 4
)

fabaceae_Cx_mode_counts_per_clade_df <- get_peaks_counts_continuous(
  fabaceae_clade_1Cx_df,
  "clade", "Cx", 2, 0.25, 1, 2
)

namecol <- "labelcountcustom"
fabaceae_clade_Cx_peaks_count_df <- make_legend_with_stats(
  fabaceae_Cx_mode_counts_per_clade_df,
  namecol, 1, TRUE
)
fabaceae_clade_1Cx_df$labelcountcustom <-
  fabaceae_clade_Cx_peaks_count_df$labelcountcustom[match(
    fabaceae_clade_1Cx_df$clade,
    fabaceae_clade_Cx_peaks_count_df$clade
  )]
desiredorder <- unique(fabaceae_clade_1Cx_df$clade)

dots_and_violin(
  fabaceae_clade_1Cx_df, "clade", "labelcountcustom", "Cx", 3,
  3, "Genome Size", desiredorder, 0.03, 0.25, 2,
  "ownwork"
)

dots_and_violin(
  fabaceae_clade_1Cx_df, "clade", "labelcountcustom", "Cx", 3,
  3, "Genome Size", desiredorder, 0.03, 0.25, 2,
  dots = FALSE
)
dots_and_violin(
  fabaceae_clade_1Cx_df, "clade", "labelcountcustom", "Cx", 3,
  3, "Genome Size", desiredorder, 0.03, 0.25, 2,
  "ownwork",
  violin = FALSE
)

---

Integrates tables and plots

Description

A series of functions to get modes/peaks from discrete and continuous variables and integrate them as tables inside plots cite as in: citation("dotsViolin")

---

Genome sizes for fabaceae

Description

fabaceae_clade_1Cx_df: parsed Cx sizes for fabaceae

Usage

fabaceae_clade_1Cx_df

Format

data.frame with columns:

name

OTU, species

clade

main fabaceae clade

Cx

genome size, Cx

See Also

get_peaks_counts_continuous

---

chromosomal counts for fabaceae

Description

fabaceae_clade_n_df: parsed n counts for fabaceae

Usage

fabaceae_clade_n_df

Format

data.frame with columns:

tip.label

OTU, species

clade

main fabaceae clade

parsed_n

chromosome number, n

See Also

get_modes_counts

---

get modes, handle ties, ignore less frequent values

Description

This function comes from an answer for a question in stackoverflow https://stackoverflow.com/questions/42698465/obtaining-3-most-common-elements-of-groups-concatenating-ties-and-ignoring-les

Usage

get_modes_counts(data, grouping_col, col2, mode_number = 3)

Arguments

data	data.frame
grouping_col	string split by this column
col2	string numerical data column
mode_number	numeric number of modes to retrieve

Value

data.frame with modes and counts per group

Examples

get_modes_counts(fabaceae_clade_n_df, "clade", "parsed_n")

---

Peaks of a continuous variable in a dataframe format

Description

This function allows you to get peaks and summary counts per group for a continuos variable in a dataframe format. Handles ties; least frequent is ignored, except if it is the only one, depends on get.peaks function

Usage

get_peaks_counts_continuous(
  origtable,
  grouping_col,
  columnname,
  peak_number,
  adjust1,
  signifi,
  nsmall
)

Arguments

origtable	dataframe
grouping_col	column with categories - character
columnname	column with numerical data
peak_number	number of peaks to get, see get.peaks
adjust1	bandwith adjust parameter
signifi	see get.peaks function
nsmall	see get.peaks function

Value

data.frame

Examples

get_peaks_counts_continuous(fabaceae_clade_1Cx_df, "clade", "Cx", 2, 0.25, 1, 2)

---

Get peaks of a continuous variable

Description

This function allows you to get peaks for a continuous variable. Based on the kernel density function

Usage

get.peaks(x, bw, signifi, nsmall, ranks = 3)

Arguments

x	dataframe
bw	bandwidth
signifi	criteria to bin the data in number of digits
nsmall	criteria to approximate (round) data
ranks	numeric how many ranks to consider

Value

data.frame

---

Make legends with stats

Description

This function merges all columns in a dataframe to be used as legends

Usage

make_legend_with_stats(
  data,
  namecol,
  start_column_idx = 2,
  first_justified_left = FALSE
)

Arguments

data	dataframe with columns to be merged into 1
namecol	name to be given to new column
start_column_idx	numeric index of first column to process
first_justified_left	boolean when TRUE justifies first column to the left, defaults to FALSE

Value

data.frame with combined source columns

Examples

fabaceae_mode_counts <- get_modes_counts(fabaceae_clade_n_df, "clade", "parsed_n")
fabaceae_clade_n_df_count <- make_legend_with_stats(fabaceae_mode_counts, "label_count", 1, TRUE)
fabaceae_Cx_mode_counts_per_clade_df <- get_peaks_counts_continuous(
  fabaceae_clade_1Cx_df,
  "clade", "Cx", 2, 0.25, 1, 2
)
namecol <- "labelcountcustom"
fabaceae_clade_1Cx_modes_count_df <- make_legend_with_stats(
  fabaceae_Cx_mode_counts_per_clade_df,
  namecol, 1, TRUE
)

---

Makes a dot-plot and violin-plot

Description

This function makes a dot-plot and violin-plot, internal function

Usage

plot_dotviolin(
  dataset,
  par,
  groupcol,
  vary,
  labelx,
  maxx,
  adjust,
  binwidth,
  fill_group = "fill_group",
  font = "mono",
  dots = TRUE,
  violin = TRUE
)

Arguments

dataset	dataframe with columns to be merged into 1
par	dot size
groupcol	categories to group
vary	numeric variable
labelx	x axis label
maxx	x axis maximum value
adjust	geom_violin adjust parameter
binwidth	geom_dotplot binwidth parameter
fill_group	2nd category with 2 options as a fill aes argument for geom_dotplot
font	font family
dots	boolean include dot plot
violin	boolean include violin plot

Value

ggplot

---