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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 recommend our users to use the paired-end sequences and the sequencing depth should be more than 70M.The length of the reads should be longer than 50bp, and longer than 100bp is the best.We absorb five kinds of common software/work to detect circRNAs, including Circexplorer2, CIRI, Find_circ, Mapsplice, and Segemehl. Users can choose one, several or all appropriate software according to their project. If our users chose several kinds of software, our pipeline will then combine all these results in to a sole matrix. To interpret the data, we design three modules to explore the identified circRNAs as well as protein coding ones, including conventional annotation, differential circRNA expression analysis, annotation and pathway enrichment. Plots and tables of analysis module are presented in a HTML file via Rmarkdown.

More information can be found in the The cirPipe workflow page, or in the project GitHub wiki. 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, plz following the step by step tutorial to run cirPipe in your local server or cluster. This tutorial 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.

Workflows

Our Pipeline Steps are showed in the below chart. CircPipe allows you to run arbitrary pipelines among five pipelines. Choose between workflows by using --selectTools.

Step Pipeline One Pipeline Two Pipeline Three Pipeline Four Pipeline Five
Raw Data QC Fastp Fastp Fastp Fastp Fastp
Reads Alignment STAR BWA Bowtie2
cirRNA identification CIRCexp lorer2 CIRI Find_circ Mapsplice Segemehl
Data Processing (in house script) Python, Java,R Python,Ja va,R Python,Ja va,R Python,Ja va,R Python,Ja va,R
Differential expression edgeR edgeR edgeR edgeR edgeR
Summary Report MultiQC+R markdown MultiQC+R markdown MultiQC+R markdown MultiQC+R markdown MultiQC+R markdown