ngstk package

Introduction

The R package ngstk can be used to facilitate the analysis of NGS data, such as visualization, conversion of the data format for WEB service input and another purpose.

In NGS data analysis process, a few of duplicated small scripts, colors theme always be created by us. In most cases, we can't use it in the future if we don't remember when and where the script be created. ngstk is a framework that can be used to collect small script, colors theme and other should be packaged material.

The purples of ngstk is that help us to manage those small scripts systematically, store some of the useful material for NGS data analysis. Especially, data visualization, conversion of data format and various database ID were the mainly mission in the recently development cycle.

Installation

CRAN

#You can install this package directly from CRAN by running (from within R):
install.packages('ngstk')

Github

# Install the cutting edge development version from GitHub:
# install.packages("devtools")
devtools::install_github("JhuangLab/ngstk")

Zip/Tarball

1. Download the appropriate zip file or tar.gz file from Github
2. Unzip the file and change directories into the configr directory
3. Run R CMD INSTALL pkg

Usage

Data format conversion

demo_file <- system.file('extdata', 'demo/proteinpaint/muts2pp_iseq.txt', package = 'ngstk')
input_data <- read.table(demo_file, sep = '\t', header = TRUE, stringsAsFactors = FALSE)
disease <- 'T-ALL'
input_data <- data.frame(input_data, disease)
input_data$disease <- as.character(input_data$disease)
# Convert mutation data to proteinpaint input
muts2mutation_mapper(input_data, input_type = 'iseq')
# Convert mutation data to cbioportal oncoprinter input
muts2oncoprinter(input_data, input_type = 'iseq')

demo_file <- system.file('extdata', 'demo/proteinpaint/fusions2pp_fusioncatcher.txt', package = 'ngstk')
input_data <- read.table(demo_file, sep = '\t', header = TRUE, stringsAsFactors = FALSE)
disease <- 'B-ALL'
sampletype <- 'diagnose'
input_data <- data.frame(input_data, disease, sampletype)
input_data$disease <- as.character(input_data$disease)
# Convert fusions data to proteinpaint input
hander_data <- fusions2pp(input_data, input_type = 'fusioncatcher')
# Convert fusions data to proteinpaint input (Meta rows)
hander_data <- fusions2pp_meta(input_data, input_type = 'fusioncatcher')

Data filtration

demo_file <- system.file("extdata", "demo/proteinpaint/fusions2pp_fusioncatcher.txt", package = "ngstk")
input_data <- read.table(demo_file, sep = "\t", header = TRUE, stringsAsFactors = FALSE)
# Get data subset according the defined rule
mhander_extra_params = list(gene_5 = 1, gene_3 = 2, any_gene = "TCF3", fusions_any_match_flag = TRUE)
result_1 <- fusions_filter(input_data, mhander_extra_params = mhander_extra_params)

mhander_extra_params = list(gene_3 = 2, right_gene = "GYPA", fusions_right_match_flag = TRUE)
result_2 <- fusions_filter(input_data, mhander_extra_params = mhander_extra_params)

mhander_extra_params = list(gene_5 = 1, left_gene = "GYPA", fusions_left_match_flag = TRUE)
result_3 <- fusions_filter(input_data, mhander_extra_params = mhander_extra_params)

mhander_extra_params = list(gene_5 = 1, gene_3 = 2, left_gene = "GYPE", right_gene = "GYPA", fusions_full_match_flag = TRUE)
result_4 <- fusions_filter(input_data, mhander_extra_params = mhander_extra_params)

mhander_extra_params = list(gene_5 = 1, gene_3 = 2, left_gene = "GYPE", right_gene = "GYPA", fusions_anyfull_match_flag = TRUE)
result_5 <- fusions_filter(input_data, mhander_extra_params = mhander_extra_params)

Tools

Some of non-core scripts or tools for NGS data analysis will be included in ngstk package. A defined markdown document will guide you to use it, such as QualityConfirm.

QualityConfirm

QualityConfirm is a quality control tool for gene panel sequencing data. Usage of QualityConfirm can be found in QualityConfirm and the demo can help you to use it more easily.

Theme

ngstk provide some of defined colors theme, you can directly download it.

Title = "ngstk theme configuration file (colors)"

[default]
colors = ["#0073c3", "#efc000", "#696969",
          "#ce534c", "#7ba6db", "#035892",
          "#052135", "#666633", "#660000", "#990000"]
[red_blue]
colors = ["#c20b01", "#196abd"]

[proteinpaint_mutations]
colors = ["#3987cc", "#ff7f0e", "#db3d3d", "#6633ff",
          "#bbbbbb", "#9467bd", "#998199", "#8c564b", "#819981",
          "#5781ff"]

[proteinpaint_domains]
colors = ["#a6d854", "#8dd3c7", "#fb8072", "#80b1d3", "#bebada", "#e5c494", "#fdb462", "#b3b3b3"]

[proteinpaint_significance]
colors = ["#aaaaaa", "#e99002", "#5bc0de", "#f04124", "#90c3d4", "#f04124", "#43ac6a"]

[adobe_color_cc_1]
colors = ["#FFE350", "#E8740C", "#FF0000", "#9C0CE8", "#0D43FF",
          "#A6B212", "#1991FF", "#ECFF00", "#CC1E14", "#B25C58"]