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Pcirc

Introduction

PCirc is a pipeline to predict plant circular RNA (CircRNA) which based on Python3. It can identify circRNA from a given RNA-seq data by high-throughput. The pipeline can alignment RNA_seq and extract features ,then based on Random Forest classification, the final circRNA will be predicted. The user only needs to run the python scripts step by step to get the predicted circular RNA.

PCirc


Requirement

Data:

  • Genome sequence (fasta format)
  • Genome annotation file (gtf/gff format)
  • RNA_seq data (fastq format)

Software:

Alignment

Predicting

python3 package:

Supported operating systems:


Download

Open the terminal and input:

git clone https://github.com/Lilab-SNNU/Pcirc.git

Usage

- You can run Pcirc step by step

  1. Alignment

    In this step need given file:

    • Genome sequence (fasta format)
    • Genome annotation file (gtf/gff format)
    • RNA_seq data (fastq format)

​ Then, you will get a file named unmapped.fasta in output_dir, it content the information of unmapped reads and will be used to the step blast

 python3 Pcirc_aligment.py -g genome.fa -G genome.gtf -o output_dir <reads_1[,reads_2]>
  1. blast

    Blast alignment of unmapped reads sequence and genomic sequences, in this step need given file:

    • Genome sequence (fasta format)
    • Unmapped reads from step Alignment (fasta format)

    Then, you will get a file named unmapped.blast in the dir which unmapped.fasta in, it content the blast information and will be used to the step Circular RNA predicting

 python3 Pcirc_unmapped_reads_blast.py -g genome.fa -q unmapped.fasta -o output_dir
  1. Circular RNA predicting

    Final this step, you will get the circular RNA information saved in a file name circ.

 python3 Pcirc_predict.py -i unmapped.blast -g genome.fa

Run example

You can download the required sra file from NCBI-SRA or fasta file from EMBL-EBI, and run Pcirc or use the test.blast run step Circular RNA predicting.


Contact us

If you encounter any problems while using Pcirc, please send an email (glli@snnu.edu.cn) or submit the issues on GitHub (https://github.com/Lilab-SNNU/Pcirc/issues) and we will resolve it as soon as possible.

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