Run CIRCexplorer2 via One Command
CIRCexplorer2 contains 5 modules and offers flexibility for multiple circular RNA analysis tasks. However, It would confuse many people who are not very familiar with CIRCexplorer2 and blocks people from making good use of it. As a result, we wrote the
fast_circ.py script to integrate different combinations of modules to complete different tasks.
Usage and option summary
fast_circ.py parse -r REF -g GENOME -t ALIGNER [--pe] [-o OUT] <fusion> fast_circ.py annotate -r REF -g GENOME -G GTF [-p THREAD] [-o OUT] <fastq>... fast_circ.py denovo -r REF -g GENOME -G GTF [-a PLUS_OUT] [-p THREAD] [-o OUT] <fastq>...
-h --help Show help message. -r REF --ref=REF Gene annotation. -g GENOME --genome=GENOME Genome FASTA file. -G GTF --gtf=GTF Annotation GTF file. -t ALIGNER Aligner (TopHat-Fusion, STAR, MapSplice, BWA, segemehl). --pe Parse paired-end alignment file (only for TopHat-Fusion). -a PLUS_OUT --pAplus=PLUS_OUT TopHat mapping directory for p(A)+ RNA-seq. -p THREAD --thread=THREAD Running threads. [default: 10] -o OUT --output=OUT Output directory. [default: circ_out]
How to use it?
fast_circ.py could perform all the circular RNA analysis pipelines mentioned in Pipelines.
- If you have mapped RNA-seq reads using one of listed aligners (TopHat2/TopHat-Fusion, STAR, segemehl and MapSplice, see here for recommended parameters of different aligners), you should use
fast_circ.py parsewith gene annotation file (via
-r) and reference genome sequence file (via
-g). Meanwhile, you should also indicate its aligner (via
-t) and whether reads are paired-end or not (via
--pe). Last but not least, the fusion junction file (
<fusion>) should be correct. This command is just like CIRCexplorer. See here for the format of gene annotation file and there for the information about how to parse different aligners.
- If you only have raw RNA-seq reads, you could use
fast_circ.py annotateto align RNA-seq reads with TopHat2/TopHat-Fusion. You should offer it gene annotation file (via
-r), gene annotation GTF file (via
-G) and reference genome sequence file (via
-g). See here for the format of gene annotation file.
fast_circ.py denovowould align raw RNA-seq reads with TopHat2/TopHat-Fusion, and de novo assemble circular RNA transcripts with Cufflinks, and last extract alternative (back-)splicing events. Some options are same with
If you offer a TopHat mapping directory for p(A)+ RNA-seq (via
fast_circ.py denovowill fetch all the alternative splicing events. Otherwise, It only fetches alternative back-splicing events. See here for more details.