Ggmanh

ggmanh

Workflows

Standard Workflow

library(ggmanh)
# Format chromosome column as a factor
simdata$chromosome <- factor(simdata$chromosome, c(1:22,"X"))
# Generate standard Manhattan plot
g1 <- manhattan_plot(x = simdata, pval.colname = "P.value", chr.colname = "chromosome", pos.colname = "position")
# Generate rescaled Manhattan plot
g2 <- manhattan_plot(x = simdata, pval.colname = "P.value", chr.colname = "chromosome", pos.colname = "position", rescale = TRUE)
# Preprocess data
mpdata <- manhattan_data_preprocess(x = simdata, pval.colname = "P.value", chr.colname = "chromosome", pos.colname = "position")
# Generate plots using preprocessed data with labels
g3 <- manhattan_plot(x = mpdata, label.colname = "label")
# Zoom into Chromosome 5
manhattan_plot(simdata, chromosome = 5, pval.colname = "P.value", chr.colname = "chromosome", pos.colname = "position")

Note: Input is a data frame of GWAS summary statistics; output is a customized Manhattan plot object.

Binned Manhattan Plot

library(ggmanh)
# Basic Binned Manhattan Plot
binned_manhattan_plot(simdata, pval.colname = "P.value", chr.colname = "chromosome", pos.colname = "position")
# Preprocess binned data
mpdat <- binned_manhattan_preprocess(simdata, pval.colname = "P.value", chr.colname = "chromosome", pos.colname = "position", bins.x = 7, bins.y = 100)
# Plot preprocessed binned data
binned_manhattan_plot(mpdat, bin.outline = TRUE)

Note: Input is a data frame of GWAS summary statistics; output is a binned grid-based Manhattan plot.

Gds Variant Annotation Plotting

library(ggmanh)
# Annotate variants using gds_annotate
simdata_label$label <- gds_annotate(x = simdata_label, annot.method = "position", chr = "chromosome", pos = "position", ref = "Reference", alt = "Alternate")
# Plot annotated data
manhattan_plot(simdata_label, pval.colname = "P.value", chr.colname = "chromosome", pos.colname = "position", label.colname = "label")

Note: Inputs are a data frame of GWAS summary statistics and a GDS file; output is an annotated Manhattan plot.

When to Use

• To visualize Genome Wide Association Study (GWAS) results using standard Manhattan plots (manhattan_plot).
• To rescale the y-axis of a Manhattan plot when highly significant p-values mask lower-significance patterns (rescale = TRUE).
• To create binned grid-based Manhattan plots for extremely large datasets to avoid plotting individual points (binned_manhattan_plot).
• To annotate variants with gene/consequence information from a GDS file using gds_annotate.

When NOT to Use

• When using discrete palettes for continuous variables (or vice versa) in binned_manhattan_plot, as the plot will fail.

Data Requirements

• Input data frame: Must contain at least three columns representing chromosome, position, and p-value.
• Chromosome column: Recommended to be formatted as a factor to avoid ambiguity in plotting order.
• GDS file: For variant annotation, a SeqArray-formatted GDS file containing annotations (e.g., annotation/symbol, annotation/consequence).

Key Parameters

• x: A data.frame, MPdata, or GRanges object containing the GWAS results.
• pval.colname: Name of the column containing p-values.
• chr.colname: Name of the column containing chromosomes.
• pos.colname: Name of the column containing genomic positions.
• rescale (FALSE): Logical indicating whether to rescale the y-axis near the significance cutoff.
• label.colname: Name of the column containing labels for annotation.
• chromosome: Specific chromosome number/name to zoom into.
• bins.x: Number of horizontal bins for the widest chromosome in binned plots.

Best Practices

• Convert the chromosome column to a factor before plotting to ensure correct ordering on the x-axis.
• Preprocess data using manhattan_data_preprocess or binned_manhattan_preprocess first if you plan to customize the plot multiple times, avoiding redundant computation.
• Set non-significant labels to "" or NA to avoid overlapping labels and extremely slow plotting times.

Common Pitfalls

• Attempting to label all points: This can cause the plotting process to take hours. Set labels for non-significant points to "" or NA.
• Using incompatible palettes: Ensure continuous palettes are used for continuous variables and discrete palettes for discrete variables in binned_manhattan_plot.

Alternatives

• qqman for basic Manhattan and QQ plots.

References

• Homepage: bioconductor.org/packages/ggmanh
• Vignette: https://bioconductor.org/packages/release/bioc/vignettes/ggmanh/inst/doc/ggmanh.html