API References

BIT(file, output_path, show=TRUE, plot.bar=TRUE, format=NULL, N=5000, bin_width=1000, burnin=NULL, genome=c("hg38", "mm10"))

Main interface to run BIT method, please set the input file path, input file format, number of iterations and bin width.

file: file path to the user-input file.

output_path: absoluate or relative directory to save the output.

show: TRUE / FALSE. Whether to display the ranking table. Default: TRUE.

plot.bar: TRUE / FALSE. Whether to plot the top 10 TRs BIT scores in a horizontal bar plot. Default: TRUE.

format: One of “bed”, “narrowPeak”, “broadPeak”, “bigNarrowPeak”, “csv”, or NULL. Specifies the format of the input file. Default: NULL. If set to NULL, BIT will automatically determine the file format based on its extension.

N: Integer. The number of iterations in the Gibbs sampler. Default: 5000.

bin_width: Integer. The width of the bin used to divide the chromatin into non-overlapping bins. Default: 1000. Only change this if you compile a different reference database.

burnin: NULL or an integer. Specifies the burn-in period when deriving the Bayesian inference for TR-level parameters. Default: NULL, which will use N/2.

genome: hg38 or mm10 for TR ChIP-seq data collected from different genome.

BIT_compare(file1, file2, output_path, show=TRUE, plot_scatter=TRUE, format=c(NULL, NULL), N=5000, bin_width=1000, burnin=NULL, genome=c('hg38', 'mm10'))

compare BIT identifid TRs for two user input epigenomic region sets.

file1: file path to the user-input file 1.

file2: file path to the user-input file 2.

output_path: absoluate or relative directory to store the Gibbs sampler data.

format: One of “bed”, “narrowPeak”, “broadPeak”, “bigNarrowPeak”, “csv”, or NULL. Specifies the format of the input file. Default: NULL. If set to NULL, BIT will automatically determine the file format based on its extension.

N: Integer. The number of iterations in the Gibbs sampler. Default: 5000.

bin_width: Integer. The width of the bin used to divide the chromatin into non-overlapping bins. Default: 1000. Only change this if you compile a different reference database.

burnin: NULL or an integer. Specifies the burn-in period when deriving the Bayesian inference for TR-level parameters. Default: NULL, which will use N/2.

genome: hg38 or mm10 for TR ChIP-seq data collected from different genome.

display_tables(file_path, output_path, burnin=NULL)

To show the ranking table by inspecting the results of Gibbs sampler.

file_path: path to the saved BIT Gibbs sampling results.

output_path: path to save the rank table.

burnin: number of samples used for burn-in. If not specify, BIT will use the half of the iterations as burn in.

rank_plot(file_path=NULL, output_path, burnin=NULL, n=10, colors="NPG", main=NULL, xlab="BIT score", ylab="TR symbols")

To draw a barplot for the top n TRs.

file_path: path to the saved BIT Gibbs sampling results.

output_path: path to save the barplot.

burnin: number of samples used for burn-in. If not specify, BIT will use the half of the iterations as burn in.

n: top n TRs will show in the barplot, default: 10.

colors: colors for each bar, default “NPG” for n<=10, has to be manually specified if n>10.

main: main title for the barplot, default: NULL.

xlab: x axis label, default: BIT score.

ylab: y axis label, default: TR symbols.

compare_scatter_plot(file1_path, file2_path, output_path, burnin=NULL)

To draw a scatterplot for the comparison bewteen two input region sets.

file1_path: path to the saved BIT Gibbs sampling results of input 1.

file2_path: path to the saved BIT Gibbs sampling results of input 2.

output_path: path to save the barplot.

burnin: number of samples used for burn-in. If not specify, BIT will use the half of the iterations as burn in.

load_chip_data(data_path, bin_width, genome=c('hg38', 'mm10'))

load the pre-compiled chip-seq data.

data_path: path to the ChIP-seq data folder, can be absolute or relative path.

bin_width width of bin, which should be in 100/500/1000 and map with your ChIP-seq data.

genome: hg38 or mm10 for TR ChIP-seq data collected from different genome.

import_input_regions(file, format=NULL, bin_width=1000, genome=c('hg38', 'mm10'))

Transform the input regions to binary vector.

file: file path to the user-input.

bin_width: desired width of bin, default: 1000.

genome: the genome of TR ChIP-seq data, either as “hg38” or “mm10”.

alignment_wrapper(input_vec, bin_width, genome=c('hg38', 'mm10'))

Count the ‘good’ and ‘informative’ cases by comparing input with the reference database.

input_vec: A input vector contains index of transformed regions by applying import_input_regions.

bin_width: desired width of bin, default: 1000.

genome: the genome of TR ChIP-seq data, either as “hg38” or “mm10”.