For more details about the package or to cite, please visit https://www.biorxiv.org/content/10.1101/2023.05.07.539760v1.

MiSiPi.RNA

Characterization of small RNA pathways

Installation and Basic Usage

You can find the full documentation and examples here.

In order to install MiSiPi.RNA, you must first install devtools and BiocManager:

install.packages("devtools")

if (!require("BiocManager", quietly = TRUE))
  install.packages("BiocManager")
  
devtools::install_github("stupornova33/MiSiPi.RNA")

library(MiSiPi.RNA)

RNAfold

In order for this package to work, you must also have RNAfold from the ViennaRNA package installed. You will need the path to the RNAfold executable. See https://www.tbi.univie.ac.at/RNA/ for installation.

Optional dependencies

For converting the .ps output files from the miRNA module to .png, install ImageMagick and ghostscript, then run

ps2png(path_to_magick_exe, file_dir)

where path_to_magick_exe is the full path to the binary executable and file_dir is the folder containing the .ps files. This will also be the output folder.

Input

The input for MiSiPi.RNA's main function is an object created by the set_vars() function. Running set_vars will always be the first step in using this package. Below is a description of each of the parameters that will be passed to set_vars(). These should be changed based on your needs.

• roi - A bed file listing your regions of interest
• bam_file - A BAM file of aligned reads. Index file must also be present
• genome - A genome fasta file. Chromosome names must match the bed file
• plot_output - (TRUE or FALSE) If TRUE, MiSiPi.RNA will output plots as pdfs
• path_to_RNAfold - Full path to RNAfold executable
• path_to_RNAplot - Full path to RNAplot executable
• pi_pal - Palette option for the generated piRNA heatmap (see below)
• si_pal - Palette option for the generated siRNA heatmap (see below)
• annotate_region - (TRUE or FALSE) Plots annotated gene features below the hairpin arc plot which is useful for characterizing cisNAT loci
• weight_reads - Determines if read counts will be weighted. ("none", "locus_norm", "weight_by_prop", or an integer)
• gtf_file - Full path to a 9 column GTF file. Required only if annotate_region is TRUE
• write_fastas - (TRUE or FALSE) If TRUE, MiSiPi.RNA will write read pairs from functions to a file. Default is FALSE
• out_type - ("pdf" or "png") Specifies the output type. Default is "pdf"

vars <- set_vars(
    roi = "path/to/bed",
    bam_file = "path/to/bam", 
    genome = "path/to/genome",
    plot_output = TRUE, 
    path_to_RNAfold = "path/to/ViennaRNA/RNAfold.exe",
    path_to_RNAplot = "path/to/ViennaRNA/RNAplot.exe",
    pi_pal = "BlYel",
    si_pal = "RdYlBl",
    annotate_region = TRUE,
    weight_reads = "none",
    gtf_file = "path/to/gtf",
    write_fastas = FALSE,
    out_type = "pdf"
)

Palettes:

Palette options are:

• "RdYlBl"
• "BlYel"
• "yelOrRed"
• "MagYel"
• "Greens"

misipi_rna()

misipi_rna(vars, method = c("all", "miRNA", "piRNA", "siRNA"))


vars <- set_vars(
    roi = "file.bed",
    bam_file = "file.bam",
    genome = "file.fa",
    plot_output = TRUE,
    path_to_RNAfold = "path/to/ViennaRNA/RNAfold.exe",
    path_to_RNAplot = "path/to/ViennaRNA/RNAplot.exe",
    pi_pal = "BlYel",
    si_pal = "RdYlBl",
    annotate_region = FALSE,
    weight_reads = "none",
    gtf_file = NULL,
    write_fastas = FALSE,
    out_type = "png"
)

misipi_rna(vars) - Default method is "all"

misipi_rna(vars, method = "siRNA")

The method parameter determines if your files will be processed for MicroRNA ("miRNA"), Piwi-interacting RNA ("piRNA"), Small interferring RNA ("siRNA"), or all three ("all").

Running with "all" method:

In addition to processing files for miRNA, piRNA, and siRNA, the "all" method outputs a table with metrics and statistics which can be used for summarization or machine learning. See the documentation for more details regarding values in table.

To make a plot summary and sortable table of results:

make_html_summary(path_to_tables = "full/path/to/run_all/", type = c("siRNA", "piRNA" or "miRNA"), ml_plots = FALSE)

The path_to_tables parameter is the path to the directory that was created when misipi_rna() was run with the "all" method. It will be called "run_all/".

The ml_plots parameter is intended for users that have already run ml_probability().

Use built-in machine learning model to characterize loci:

See full documentation for more details.

ml_probability(path_to_table = "full/path/to/run_all/", table = "table_ml.txt")

The path_to_table parameter is the path to the directory that was created when misipi_rna() was run with the "all" method. It will be called "run_all/".