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Manhattan plots

Source: R/turboman.r
turboman.Rd

Manhattan plots

Usage

turboman(
  input_data_path,
  custom_peak_annotation_file_path,
  reference_file_path,
  pvalue_sign,
  plot_title,
  vertical_resolution = 1800
)

Arguments

input_data_path

Path of the input association data.

custom_peak_annotation_file_path

Path of the custom annotation of variants.

reference_file_path

Path to the 'turboman_hg19_reference_data.rda' / 'turboman_hg19_reference_data.rda' reference file.

pvalue_sign

Significance threshold p-value.

plot_title

Plot title which will be displayed on top of the plot.

vertical_resolution

A fixed number of points (pixels) to be plotted vertically.

Details

Input association data file / input_data_path

Define the path of the input association data. The input data needs to be a file that has:

  1. Spaces as field separators.

  2. One header line.

  3. Option I. (no extreme p-values present): 3 columns, being chromosome, position, pvalue in order, column names are not important. Option II. (extreme p-values present): 5 columns, being chromosome, position, pvalue, beta, se in order, column names are not important.

Custom annotation file / custom_peak_annotation_file_path

Define the path of the custom annotation of variants. The input data needs to be a file that has:

  1. Spaces / tabs as field separators.

  2. One header line with exact column names (order not important).

  3. Columns: chromosome, position, label (e.g., gene name) / nearest_gene_name, cis/trans flag (optional). NB!: If no label is given, variants will be automatically annotated

Reference file / reference_file_path

Define the path to the 'turboman_hg19_reference_data.rda' / 'turboman_hg38_reference_data.rda' reference file that contains the LD block breaks as in Berisa and Pickrell (2016) and gene coordinates used to construct and annotate the Manhattan plot. Both are available from the turboman directory of the installed package, e.g., file.path(find.package('pQTLtools'),'turboman','turboman_hg38_reference_data.rda').

Significance threshold p-value / pvalue_sign

Define the significance threshold. This will be used to

  1. Highlight signal peaks that come above this significance threshold.

  2. Annotate the nearest gene to the top signal in the peak.

  3. Draw a horizontal reference line equal to this threshold.

Title of the plot / plot_title

Define title on top of the plot.

Number of pixels on vertical axis / vertical_resolution

Define a fixed number of points (pixels) on vertical axis.

References

Berisa T, Pickrell JK (2016). “Approximately independent linkage disequilibrium blocks in human populations.” Bioinformatics, 32(2), 283-285. doi:10.1093/bioinformatics/btv546 .

Author

Arthur Gilly, Chris Finan, Bram Prins, see https://github.com/bpprins/turboman.

Examples

if (FALSE) {
# Screen output
require(gap.datasets)
test <- mhtdata[c('chr','pos','p')]
write.table(test,file='test.txt',row.names=FALSE,quote=FALSE)
annotate <- subset(mhtdata[c('chr','start','gene','p')],p<5e-8 & gene!='')
names(annotate) <- c('chromosome','position','nearest_gene_name','p')
write.table(unique(annotate[,-4]),file='annotate.txt',row.names=FALSE,quote=FALSE)
input_data_path <- 'test.txt'
custom_peak_annotation_file_path <- 'annotate.txt'
reference_file_path <-
  file.path(find.package('pQTLtools'),'turboman','turboman_hg19_reference_data.rda')
pvalue_sign <- 5e-8
plot_title <- 'gap.datasets example'
turboman(input_data_path, custom_peak_annotation_file_path,
         reference_file_path, pvalue_sign, plot_title)
# Figure shown on https://github.com/jinghuazhao/tests/tree/main/turboman
png('IL12B.png',width=3600, height=3600, pointsize = 12, res=450)
input_data_path <- 'IL.12B.txt.gz'
custom_peak_annotation_file_path <- 'IL.12B.annotate'
reference_file_path <-
  file.path(find.package('pQTLtools'),'turboman','turboman_hg19_reference_data.rda')
pvalue_sign <- 5e-8
plot_title <- 'IL12B'
turboman(input_data_path, custom_peak_annotation_file_path,
         reference_file_path, pvalue_sign, plot_title)
dev.off()
}