ruy204 / FiTnEss-1

A statistical model to analyze Tn-seq data

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

FiTnEss

Finding Tn-Seq Essential genes (FiTnEss)

FiTnEss is a package using Transposon insertion sequencing data to identify essential genes in the genome.

Original paper on bioRxiv: Defining the core essential genome of Pseudomonas aeruginosa

Quick start

After installing FiTnEss package, run main FiTnEss function by FiTnEss_Run

Function arguments

Arguments in this function include:

  • strain
  • file_location: path and name of tally file for run: e.g. "/home/your_folder/your_tally.txt"
  • permissive_file: path and name of non-permissive TA site file that generated from genomic pre-processing step: e.g. "/home/your_folder/non_permissive_TA_sites.txt"
  • homologous_file: path and name of homologous TA site file that generated from pre-processing step: e.g. "/home/your_folder/homologous_TA_sites.txt"
  • gene_file: path and name of GFF3 gene file that downloaded from Pseudomonas Genome Database: e.g. "/home/your_folder/PA14_gene_file.txt"
  • save_location: path and name of where to save final results file: e.g. "/home/results_folder/results.xlsx"
  • repeat_time: how many times to run the pipeline in order to obtain best results: by default, we run 3 times.

Step 1. install dependent packages

install.packages(c("devtools","dplyr","fBasics","goftest","openxlsx","scales","stats","tidyr"))

Step 2. install FiTnEss package from github

devtools::install_github("ruy204/FiTnEss")

Step 3. load FiTnEss and dependent packages

Packages <- c("devtools","dplyr","fBasics","goftest","openxlsx","scales","stats","tidyr")
lapply(Packages, library, character.only = TRUE)

require(FiTnEss)

Step 4. run FiTnEss

FiTnEss_Run("UCBPP",
            "/home/TnSeq/data/test_data/PA14_M9_rep1_tally.txt",
            "/home/TnSeq/data/test_data/nonpermissive_TA_sites.txt",
            "/home/TnSeq/data/test_data/homologous_TA_sites.txt",
            "/home/TnSeq/data/test_data/PA14_gene_file.txt",
            "/home/TnSeq/test_result/test_results.xlsx",
            repeat_time = 3)

About

A statistical model to analyze Tn-seq data


Languages

Language:HTML 93.7%Language:R 4.4%Language:Python 1.2%Language:Shell 0.6%