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In a nutshell, circPipe (circRNAs Pipeline) aims at data exploration of circRNAs. It begins with the raw sequencing data and then following a step of quality control. We absorb five kind of common software to detect circRNAs,including Circexplorer2, CIRI, Find_circ, Mapsplice and Segemehl. Users can choose One,several or all appropriate software as their own pleasure.By default,our pipeline will use all the five software to detect circRNAs respectively. After combining all these results,we design 3 modules to analyze the data, including annotation, differential gene expression analysis and correlation analysis.Plots and tables of analysis module are presented in HTML file via Rmarkdown.
More information can be found in the The cirPipe workflow page, or in the project GitHub README. Please be sure that you have all dependencies software or tools preinstalled in you system. Otherwise, we recommended that users employ docker or singularity containers to run the pipe.
This wiki includes several tutorials, but we recommend to get start with the How to run cirPipe tutorial. This tutorial will explain how to set the parameters in the nextflow.config file, and describe the files that will be produced in output, while at this page you can know more about How to read the logs.
Our Pipeline Steps are showed in the below chart.
The pipeline allows you to choose between running either replicates or without replicates.Choose between workflows by using --without_replicate
or not(default) .
Step | Pipeline One | Pipeline Two | Pipeline Three | Pipeline Four | Pipeline Five |
---|---|---|---|---|---|
Raw Data QC | Fastp | Fastp | Fastp | Fastp | Fastp |
Reads Alignment | STAR | BWA | Bowtie2 | - | - |
Reads counting | CIRCexplorer2 | CIRI | Find_circ | Mapsplice | Segemehl |
Data Processing (in house script) | Python,JAVA,R | Python,JAVA,R | Python,JAVA,R | Python,JAVA,R | Python,JAVA,R |
Differential expression | edgeR | edgeR | edgeR | edgeR | edgeR |
Summary Report | MultiQC | MultiQC | MultiQC | MultiQC | MultiQC |
2018-2019 Center for Bioinformatics, Sun Yat-sen University Cancer Center