Skip to content

riccabolla/PCNE_paper_script

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

67 Commits
 
 
 
 

Repository files navigation

PCNE workflow

Tutorial to reproduce data presented in the paper: PCNE: a tool for plasmid copy number estimation.

Requirements

All the required files (reads, assemblies ...) are available here: https://doi.org/10.5281/zenodo.17550873

The following tools and relative dependencies are required:

All the analyses have been performed in a separate conda env

conda create -n pcne -c bioconda pcne
conda create -n mobsuite -c bioconda mob_suite
conda create -n platon -c bioconda platon
conda create -n shovill -c bioconda shovill
conda create -n art -c bioconda art
conda create -n iss -c bioconda insilicoseq
conda create -n abricate -c bioconda abricate

For further details, look at the respective documentation pages.

Simulated dataset

Hardware

All scripts require 5 CPUs and 16 GB of RAM maximum.

File preparation

Go to the working directory and put the chromosome and plasmid files in it.

Generate reads

In the working directory, execute the script art.sh and iss.sh

Test PCNE

In the working directory, execute the script pcne_50x.sh.

Assembly simulated reads

In the working directory, execute the script shovill.sh

Test PCNE + Platon

First, download the platon database following instructions, and put it in the working directory.
In the working directory, execute the script pcne_platon.sh

Test PCNE + MOBSuite

In the working directory, execute the script pcne_mobsuite.sh

Real dataset

Hardware

To reproduce real data, 5 cpus and 32 GB of memory are required

File preparation

Download filtered reads directly from https://doi.org/10.5281/zenodo.17550873, or in alternative you can use prefetch following the instructions.
WGS reads are deposited at SRA archive under BioProject PRJNA1044738
Once downloaded, rename the reads as their sample name (ex. EM4N2)
To filter reads use FastP setting quality filter -q 30

Assembly

Put the reads in a folder named "Real_data_reads", and from working directory launch real_data_assembly.sh

Plasmid identification

From working directory run platon_real_data.sh

PCNE

From working directory run pcne_real_data.sh

Case study

Hardware

To reproduce real data, 5 cpus and 32 GB of memory are required

File preparation

Download filtered reads directly from https://doi.org/10.5281/zenodo.17550873, or in alternative raw reads from SRA.
Once downloaded, rename the reads as their sample name (KP_01, ...)
To filter reads use FastP setting quality filter -q 30

Assembly

Put reads in a folder named "Case_study_reads", and from working directory launch case_study_shovill.sh.

Plasmid identification

From working directory run case_study_mobsuite.sh

Abricate

From working directory run case_study_abricate.sh

PCNE

From working directory run case_study_pcne.sh

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages