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Welcome to the cirPipe wiki!

In a nutshell, cirPipe (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, before running cirPipe, check if you have all the dependencies installed, as explained in the Getting started section and in the project GitHub README.

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