Ciri Ciri Vista Window

Introduction

Sailfish-cir is a computational tool to estimate the relative abundance of circular RNA transcripts from high-throughput RNA-seq data.

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It accepts output of circRNA identification tools (CIRI, KNIFE, circRNA_finder) or a BED-format file to specify the reference set of circular RNA transcripts in RNA-seq data. Then, it transforms all circular transcripts to pseudo-linear transcripts. Finally, it estimates the expression of both linear and circular transcripts using Sailfish framework.

Prerequisites

The following three tools should be installed before running Sailfish-cir.

We assume these pre-installed tools are running under a Unix-like environment, and paths of gffread and sailfish binary executive should be added to your PATH variable.

Other than above third party tools, several data files are required for Sailfish-cir as well.

Usage

Output file

Sailfish-cir expression estimats can be found at a subdirectory named quant_circular under the path set by -o parameter.

Notes

1. .gtf file

   In order to generate reference sequences of circular RNA transcripts, a database of your genomic annotation is needed. It is recommended to create the database file manually using the same filename with extension '.db' in the same directory. Since gffutils don't guess GTF file format, and GTF format was changed after GRCH37.75. It will be time-consuming when building the database using the same option for earlier gtf version.

2. output file from circRNA identification tools

   This script accepts BED-format file or output files of circRNA identification tools (CIRI, circRNA_finder, KNIFE are supported) to specify the circular RNA transcripts.

   We also provide a small utility to convert those outputs to a BED-format file.usage as follows:

   For CIRI, this will create a .bed file in the same folder. the 'name' (4th) column follows this 'circular_transcript@host_gene' pattern.For KNIFE, this will create a 'summarized_knife_junction.bed' under your KNIFE output folder.circRNA_finder output is actually BED-format.

   If you want to quantify circRNA from multiple circRNA detection results, convert those output files into BED format and merge them into a single .bed file, then use '--bed' option.

   

ChangeLog

Release v0.11

• BED-file format support: use '--bed' option to input a bed file as the reference set of circular RNA transcripts
• Convert utility: convert CIRI outputs into a BED-file format
• Issue of effective length correction: fix the effective length correction when estimating circular RNA expression values in real rRNA-depleted RNA-seq data. Please use '--mll' to specify the estimated effective fragment length of RNA-seq data.
• Add some filters to unclutter the GTF entries.

Release v0.10

• the first version. Snapshot with documents is here.

Example files

Example files are available in MEGA

1. Human gene Annotation file: hg19 gtf fileOR binary database file by gffutils

2. Genome sequence file: hg19 fasta file

3. Sailfish (ver 0.9.0): Sailfish Linux binary

4. RNA-seq simulation scripts simulation

5. Simulated RNA-seq datasets11 simulated datasets (uniform expresion distribution)

   uniform sequencing error with error rate 0.01, script and other files

   uniform sequencing error with error rate 0.02, script and other files

   empirical error model: illumina 4, script and other files

   empirical error model: illumina 5, script and other files

   simulation size two fold, script and other files

   simulation size 4 fold, script and other files

   simulation using whole genome, script and other files

Reference

Musheng Li, Xueying Xie, Jing Zhou, Mengying Sheng, Xiaofeng Yin, Eun-A Ko, Tong Zhou* and Wanjun Gu*. Quantifying circular RNA expression from RNA-seq data using model-based framework. Bioinformatics, 2017, in press.

Contact

Musheng Li (zerodel@126.com)