Package 'hidecan'

Description

Add data type to HIDECAN plot

Usage

.add_data_type(
  p,
  toplot,
  i,
  paes,
  add_new_legend,
  point_size,
  label_size,
  label_padding
)

Arguments

Value

ggplot p to which the new data type has been added.

Description

Check chromosome limits

Usage

.check_chrom_limits(chrom_limits, chrom_length, chroms)

Arguments

Value

Tibble of chromosome limits to use in the plot.

Description

Check chromosomes to plot

Usage

.check_chroms(toplot, chrom_length, chroms, remove_empty_chrom)

Arguments

Value

Character vector of chromosomes to plot.

Description

Checks whether some columns are present in a tibble

Usage

.check_cols(x, col_names, param_name = "Input data-frame")

Arguments

Value

invisible NULL

Description

Computes the length (in bp) of each chromosome as the maximum position of genes on the chromosome.

Usage

.compute_chrom_length_genes(x)

Arguments

Value

A tibble with two columns: chromosome (chromosome name) and length (chromosome length in base pair).

Description

Computes the length (in bp) of each chromosome as the maximum position of chromosomes on the chromosome.

Usage

.compute_chrom_length_markers(x)

Arguments

Value

A tibble with two columns: chromosome (chromosome name) and length (chromosome length in base pair).

Description

Returns either "aes_type" attribute or object class

Usage

.get_aes_type(x)

Arguments

Value

Either "aes_type" attribute or object class.

Description

Get the list of aesthetics for each data types in the plot.

Usage

.get_plot_aes(aes_types, colour_genes_by_score, custom_aes)

Arguments

Value

Named list of plot aesthetics.

Description

Filters markers, genes/transcripts or QTL regions based on a threshold applied to their GWAS, DE or QTL score, and log2(fold-change) (if applicable). For a set of candidate genes, simply returns the list. Note that markers, genes and QTL regions with a missing score or log2(fold-change) will be removed from the dataset.

Usage

apply_threshold(x, score_thr = 0, log2fc_thr = 0)

## S3 method for class 'GWAS_data'
apply_threshold(x, score_thr = 0, log2fc_thr = 0)

## S3 method for class 'DE_data'
apply_threshold(x, score_thr = 0, log2fc_thr = 0)

## S3 method for class 'CAN_data'
apply_threshold(x, score_thr = 0, log2fc_thr = 0)

## S3 method for class 'QTL_data'
apply_threshold(x, score_thr = 0, log2fc_thr = 0)

## S3 method for class 'CUSTOM_data'
apply_threshold(x, score_thr = 0, log2fc_thr = 0)

## Default S3 method:
apply_threshold(x, score_thr = 0, log2fc_thr = 0)

Arguments

Value

A filtered tibble (of class GWAS_data_thr, DE_data_thr, CAN_data_thr, QTL_data_thr or CUSTOM_data_thr).

Examples

x <- get_example_data()

## For GWAS results
apply_threshold(GWAS_data(x[["GWAS"]]), score_thr = 4)

## For DE results - in second line, no threshold is applied
## on the log2(fold-change)
apply_threshold(DE_data(x[["DE"]]), score_thr = -log10(0.05), log2fc_thr = 1)
apply_threshold(DE_data(x[["DE"]]), score_thr = -log10(0.05), log2fc_thr = 0)

## No effect on the Candidate genes
apply_threshold(CAN_data(x[["CAN"]]))

## For QTL mapping results
apply_threshold(QTL_data(x[["QTL"]]), score_thr = 4)

Description

Creates a CAN_data object from a tibble or data-frame of candidate genes.

Usage

CAN_data(dat, keep_rownames_as = NULL)

Arguments

Details

The input data should have one row per gene, and at least the following columns:

• chromosome: character column, chromosome on which the gene is located.

• start and end: numeric, starting and end position of the gene (in bp). A column position will be constructed as the middle value (mean) between start and end.

• name: character, the name of the candidate genes to be displayed.

Value

A CAN_data object, i.e. a tibble.

Examples

x <- get_example_data()

CAN_data(x[["CAN"]])

Description

Computes the length (in bp) of each chromosome from a list of GWAS and DE results as well as candidate gene lists.

Usage

combine_chrom_length(x)

Arguments

Value

A tibble with two columns: chromosome (chromosome name) and length (chromosome length in base pair).

Examples

x <- get_example_data()
y <- list(
  "GWAS" = GWAS_data(x[["GWAS"]]),
  "DE" = DE_data(x[["DE"]]),
  "CAN" = CAN_data(x[["CAN"]]),
  "QTL" = QTL_data(x[["QTL"]])
)

combine_chrom_length(y)

Description

Computes the length (in bp) of each chromosome as the maximum position of markers or genes on the chromosome.

Usage

compute_chrom_length(x)

## S3 method for class 'GWAS_data'
compute_chrom_length(x)

## S3 method for class 'DE_data'
compute_chrom_length(x)

## S3 method for class 'CAN_data'
compute_chrom_length(x)

## S3 method for class 'QTL_data'
compute_chrom_length(x)

## S3 method for class 'CUSTOM_data'
compute_chrom_length(x)

Arguments

Value

A tibble with two columns: chromosome (chromosome name) and length (chromosome length in base pair).

Examples

x <- get_example_data()

compute_chrom_length(GWAS_data(x[["GWAS"]]))
compute_chrom_length(DE_data(x[["DE"]]))
compute_chrom_length(CAN_data(x[["CAN"]]))
compute_chrom_length(CAN_data(x[["QTL"]]))

Description

Creates a HIDECAN plot from a list of filtered GWAS or DE results and/or candidate genes.

Usage

create_hidecan_plot(
  x,
  chrom_length,
  colour_genes_by_score = TRUE,
  remove_empty_chrom = FALSE,
  chroms = NULL,
  chrom_limits = NULL,
  title = NULL,
  subtitle = NULL,
  n_rows = NULL,
  n_cols = 2,
  legend_position = "bottom",
  point_size = 3,
  label_size = 3.5,
  label_padding = 0.15,
  line_alpha = 0.7,
  rect_alpha = 0.3,
  custom_aes = NULL
)

Arguments

Value

A ggplot.

Examples

if (interactive()) {
x <- get_example_data()
y <- list("QTL" = QTL_data(x[["QTL"]]),
          "GWAS" = GWAS_data(x[["GWAS"]]),
          "DE" = DE_data(x[["DE"]]),
          "CAN" = CAN_data(x[["CAN"]]))

chrom_length <- combine_chrom_length(y)

z <- list(
  apply_threshold(y[["QTL"]], score_thr = 4),
  apply_threshold(y[["GWAS"]], score_thr = 4),
  apply_threshold(y[["DE"]], score_thr = 1.3, log2fc_thr = 0.5),
  apply_threshold(y[["CAN"]])
)

create_hidecan_plot(z,
                    chrom_length,
                    label_size = 2)

## Colour genes according to their fold-change
create_hidecan_plot(z,
                    chrom_length,
                    colour_genes_by_score = FALSE,
                    label_size = 2)

## Add names to the datasets
create_hidecan_plot(setNames(z, c("Genomics", "RNAseq", "My list")),
                    chrom_length,
                    colour_genes_by_score = FALSE,
                    label_size = 2)

## Add names to some of the datasets only (e.g. not for GWAS results)
create_hidecan_plot(setNames(z, c(" ", "RNAseq", "My list")),
                    chrom_length,
                    colour_genes_by_score = FALSE,
                    label_size = 2)

## Set limits on all chromosomes (to "zoom in" to the 10-20Mb region)
create_hidecan_plot(z,
                    chrom_length,
                    label_size = 2,
                    chrom_limits = c(10e6, 20e6))

## Set limits on some chromosomes only
create_hidecan_plot(z,
                    chrom_length,
                    label_size = 2,
                    chrom_limits = list("ST4.03ch00" = c(10e6, 20e6),
                                        "ST4.03ch02" = c(15e6, 25e6)))
}

Description

Creates a CUSTOM_data object from a tibble or data-frame of custom genomic features.

Usage

CUSTOM_data(dat, keep_rownames_as = NULL)

Arguments

Details

The input data should have one row per marker, and at least the following columns:

• chromosome: character column, chromosome on which the feature is located.

• position: numeric, the physical position of the feature along the chromosome (in bp) OR

• start and end: numeric, starting and end position of the feature (in bp). If there is no position column, it will be constructed as the middle value (mean) between start and end. If there is a position column but no start and/or end columns, these will be set to the values in the position column.

• score: numeric, score to be used for the genomic feature.

Value

A CUSTOM_data object, i.e. a tibble.

Examples

x <- get_example_data()

CUSTOM_data(x[["GWAS"]])

Description

Creates a DE_data object from a tibble or data-frame of differential expression results.

Usage

DE_data(dat, keep_rownames_as = NULL)

Arguments

Details

The input data should have one row per gene or transcript, and at least the following columns:

• chromosome: character column, chromosome on which the gene/transcript is located.

• start and end: numeric, starting and end position of the gene/transcript (in bp). A column position will be constructed as the middle value (mean) between start and end.

• score or padj: numeric, the DE score or adjusted p-value of the gene/transcript. If column score column is missing, will be constructed as -log10(padj).

• foldChange or log2FoldChange: numeric, the fold-change or log2(fold-change) of the gene/transcript. If column log2FoldChange is missing, will be constructed as log2(foldChange).

Value

A DE_data object, i.e. a tibble.

Examples

x <- get_example_data()

DE_data(x[["DE"]])

Description

Returns a list of example datasets.

Usage

get_example_data()

Details

The dataset used in this example is presented in: Angelin-Bonnet et al., BMC Plant Biology (2023). In this study, tetraploid potato plants from a half-sibling breeding population were used to assess the genetic components of tuber bruising. Capture sequencing was used to obtain genomic information about the individuals, and a genome-wide association study (GWAS) was performed on 72,847 genomic biallelic variants obtained from 158 plants for which a bruising score was measured. The GWAS analysis was carried with the GWASpoly package. In addition, expression data was obtained for 25,163 transcribed genes, and a differential expression (DE) analysis was carried out between 41 low- and 33 high-bruising samples. Finally, a literature search yielded a list of 42 candidate genes identified in previous studies as involved in potato tuber bruising mechanisms. A subset of the GWAS and DE results, as well as the list of candidate genes from the literature, are made available in this function. From the complete GWAS results table, half of the genomic variants with a GWAS score < 3.5 were randomly selected and consequently discarded, yielding a dataset with GWAS scores for 35,481 variants. Similarly, half of the transcribed genes in the DE results table with an adjusted p-value > 0.05 were randomly selected and discarded, yielding a dataset with DE results for 10,671 transcribed genes. This filtering was performed to reduce the size of the datasets (in accordance with CRAN policies), but ensures that all significant markers and genes are retained in the datasets. Finally, some of the candidate genes located on chromosome 3 were removed from the example dataset for better clarity in the resulting HIDECAN plot, leaving 32 candidate genes. The QTL mapping data was randomly generated for illustration purposes, as no QTL mapping was performed in the original study.

Value

A list with the following elements:

• QTL: a tibble of QTL regions, with columns id, chromosome, start, end, score and name.

• GWAS: a tibble of GWAS results, with columns id, chromosome, position and score.

• DE: a tibble of differential expression results, with columns gene, chromosome, padj, log2FoldChange, start, end and label.

• CAN: a tibble of candidate genes, with columns id, chromosome, start, end, name and gene_name.

Description

Creates a GWAS_data object from a tibble or data-frame of GWAS results.

Usage

GWAS_data(dat, keep_rownames_as = NULL)

Arguments

Details

The input data should have one row per marker, and at least the following columns:

• chromosome: character column, chromosome on which the marker is located.

• position: numeric, the physical position of the marker along the chromosome (in bp).

• score or padj: numeric, the GWAS score or adjusted p-value of the marker. If column score column is missing, will be constructed as -log10(padj).

Value

A GWAS_data object, i.e. a tibble.

Examples

x <- get_example_data()

GWAS_data(x[["GWAS"]])

Description

Extracts GWAS results and chromosome length from GWASpoly output.

Usage

GWAS_data_from_gwaspoly(gwaspoly_output, traits = NULL, models = NULL)

Arguments

Value

A list with the following elements:

• gwas_data_list: A named list of GWAS_data objects, giving the markers score for each possible trait/genetic model combination. The names of the list are in the form ⁠trait (genetic model)⁠.

• gwas_data_thr_list: if the input data is a GWASpoly.thresh object (from the GWASpoly::set.threshold() function), a named list of GwAS_data_thr, with the significant markers score for each possible trait/genetic model combination. The names of the list are in the form ⁠trait (genetic model)⁠.

• chrom_length: A tibble with one row per chromosome, giving the length (in bp) of each chromosome.

Description

Generates a list of the default aesthetics used for HIDECAN plots.

Usage

hidecan_aes(colour_genes_by_score = TRUE)

Arguments

Value

A named list, with one element per type of data (e.g. GWAS, DE, etc). Each element is itself a list with the following elements:

• y_label: prefix added to the name of a track on the y-axis of the plot.

• show_as_rect: logical, whether the interval should be represented by a point showing its mid-position (FALSE), or by a rectangle spanning its length (TRUE).

• line_colour: colour of the vertical line used to show the position of elements of this type.

• point_shape: shape used for the points of this type. Non-applicable if show_as_rect is TRUE.

• show_name: whether a label with name value should be added to points of this type.

• fill_scale: fill scale to use for the points of this type.

• rect_width: if show_as_rect is TRUE, relative half-width of the rectangles (in terms of space between two tracks).

Description

Wrapper function to create a HIDECAN plot from GWAS results, DE results or candidate genes.

Usage

hidecan_plot(
  qtl_list = NULL,
  gwas_list = NULL,
  de_list = NULL,
  can_list = NULL,
  score_thr_qtl = 4,
  score_thr_gwas = 4,
  score_thr_de = 2,
  log2fc_thr = 1,
  chrom_length = NULL,
  colour_genes_by_score = TRUE,
  remove_empty_chrom = FALSE,
  chroms = NULL,
  chrom_limits = NULL,
  title = NULL,
  subtitle = NULL,
  n_rows = NULL,
  n_cols = 2,
  legend_position = "bottom",
  point_size = 3,
  label_size = 3.5,
  label_padding = 0.15,
  line_alpha = 0.7,
  rect_alpha = 0.3,
  custom_aes = NULL,
  custom_list = NULL,
  score_thr_custom = 0
)

Arguments

Value

a ggplot.

Examples

if (interactive()) {
x <- get_example_data()

## Typical example with one GWAs result table, one DE result table and
## one table of candidate genes
hidecan_plot(qtl_list = x[["QTL"]],
             gwas_list = x[["GWAS"]],
             de_list = x[["DE"]],
             can_list = x[["CAN"]],
             score_thr_qtl = -log10(0.0001),
             score_thr_gwas = -log10(0.0001),
             score_thr_de = -log10(0.005),
             log2fc_thr = 0,
             label_size = 2)

## Example with two sets of GWAS results
hidecan_plot(gwas_list = list(x[["GWAS"]], x[["GWAS"]]),
             score_thr_gwas = 4)

## Example with two sets of DE results, with names
hidecan_plot(de_list = list("X vs Y" = x[["DE"]],
                            "X vs Z" = x[["DE"]]),
             score_thr_de = -log10(0.05),
             log2fc_thr = 0)

## Set limits on all chromosomes (to "zoom in" to the 10-20Mb region)
hidecan_plot(qtl_list = x[["QTL"]],
             gwas_list = x[["GWAS"]],
             de_list = x[["DE"]],
             can_list = x[["CAN"]],
             score_thr_qtl = -log10(0.0001),
             score_thr_gwas = -log10(0.0001),
             score_thr_de = -log10(0.005),
             log2fc_thr = 0,
             label_size = 2,
             chrom_limits = c(10e6, 20e6))

## Set limits on some chromosomes only
hidecan_plot(qtl_list = x[["QTL"]],
             gwas_list = x[["GWAS"]],
             de_list = x[["DE"]],
             can_list = x[["CAN"]],
             score_thr_qtl = -log10(0.0001),
             score_thr_gwas = -log10(0.0001),
             score_thr_de = -log10(0.005),
             log2fc_thr = 0,
             label_size = 2,
             chrom_limits = list("ST4.03ch00" = c(10e6, 20e6),
                                  "ST4.03ch02" = c(15e6, 25e6)))
}

Description

Creates a HIDECAN plot from the GWAS results from GWASpoly.

Usage

hidecan_plot_from_gwaspoly(gwaspoly_output, traits = NULL, models = NULL, ...)

Arguments

Value

A ggplot.

Description

Creates a Manhattan plot from a data-frame of GWAS results.

Usage

manhattan_plot(
  gwas_list,
  score_thr = NULL,
  chroms = NULL,
  title = NULL,
  subtitle = NULL,
  size_range = c(1, 3),
  chrom_col = NULL,
  ncol = NULL
)

Arguments

Value

A ggplot.

Examples

if (interactive()){
x <- get_example_data()[["GWAS"]]

manhattan_plot(x)

## Adding a significance threshold line in the plot
manhattan_plot(x, score_thr = 4)


## Use only two colours for the chromosomes
manhattan_plot(x,
               score_thr = 4,
               chrom_col = c("dodgerblue1", "dodgerblue4"))
}

Description

CAN_data constructor

Usage

new_CAN_data(dat)

Arguments

Value

A CAN_data object, i.e. a tibble.

Description

CUSTOM_data constructor

Usage

new_CUSTOM_data(dat)

Arguments

Value

A GWAS_data object, i.e. a tibble.

Description

DE_data constructor

Usage

new_DE_data(dat)

Arguments

Value

A DE_data object, i.e. a tibble.

Description

GWAS_data constructor

Usage

new_GWAS_data(dat)

Arguments

Value

A GWAS_data object, i.e. a tibble.

Description

QTL_data constructor

Usage

new_QTL_data(dat)

Arguments

Value

A QTL_data object, i.e. a tibble.

Description

Creates a QTL_data object from a tibble or data-frame of QTL mapping results.

Usage

QTL_data(dat, keep_rownames_as = NULL)

Arguments

Details

The input data should have one row per QTL region, and at least the following columns:

• chromosome: character column, chromosome on which the QTL region is located.

• start and end: numeric, starting and end position of the QTL region (in bp). A column position will be constructed as the middle value (mean) between start and end.

• score or padj: numeric, the QTL score or adjusted p-value of the QTL region. If column score column is missing, will be constructed as -log10(padj).

Value

A QTL_data object, i.e. a tibble.

Examples

x <- get_example_data()

QTL_data(x[["QTL"]])

Description

Starts the HIDECAN shiny app. The app reads in csv data to produce a HIDECAN plot.

Usage

run_hidecan_shiny()

Value

No return value, called for side effects (launching the shiny app).

Description

Checks validity of input for CAN_data constructor

Usage

validate_CAN_data(x)

Arguments

Value

A CAN_data object, i.e. a tibble.

Description

Checks validity of input for CUSTOM_data constructor

Usage

validate_CUSTOM_data(x)

Arguments

Value

A CUSTOM_data object, i.e. a tibble.

Description

Checks validity of input for DE_data constructor

Usage

validate_DE_data(x)

Arguments

Value

A DE_data object, i.e. a tibble.

Description

Checks validity of input for GWAS_data constructor

Usage

validate_GWAS_data(x)

Arguments

Value

A GWAS_data object, i.e. a tibble.

Description

Checks validity of input for QTL_data constructor

Usage

validate_QTL_data(x)

Arguments

Value

A QTL_data object, i.e. a tibble.