Package: circtools
a one-stop software solution for circular RNA researchIntroductionCircular RNAs (circRNAs) originate through back-splicing events from linear primary transcripts, are resistant to exonucleases, typically not polyadenylated, and have been shown to be highly specific for cell type and developmental stage. Although few circular RNA molecules have been shown to exhibit miRNA sponge function, for the vast majority of circRNAs however, their function is yet to be determined.The prediction of circular RNAs is a multi-stage bioinformatics process starting with raw sequencing data and usually ending with a list of potential circRNA candidates which, depending on tissue and condition may contain hundreds to thousands of potential circRNAs. While there already exist a number of tools for the prediction process (e.g.DCCandCircTest), publicly available downstream analysis tools are rare.We developedcirctools, a modular, Python3-based framework for circRNA-related tools that unifies several functionalities in single command line driven software. The command line follows thecirctools subcommandstandard that is employed in samtools or bedtools. Currently, circtools includes modules for detecting and reconstructing circRNAs,
a quick check of circRNA mapping results, RBP enrichment screenings, circRNA primer design, statistical testing, and an exon usage module.DocumentationClickhereto access the complete documentation on Read the Docs.InstallationThecirctoolspackage is written in Python 3 (supporting Python 3.7 - 3.10). It requires only a small number of external dependencies, namely standard bioinformatics tools:bedtools (>= 2.27.1)[RBP enrichment module, installed automatically]R (>= 4.0)[Data visualization and data processing]Installation is managed throughpip3 install circtoolsorpython3 setup.py installwhen installed from the cloned GitHub repository. No sudo access is
required if the installation is executed with--userwhich will install the
package in a user-writeable folder. The binaries should be installed
to/home/$user/.local/bin/in case of Debian-based systems.circtoolswas developed and tested on Debian Buster, but should also
run with any other distribution.The installation can be performed directly from Pypi:#installcirctoolspip install numpy # required for HTSeq, a dependency of circtools
pip install circtools#installRpackagesforcirctoolscirctools_install_R_dependenciesAdditionally, this repository offers the latest development version:pip install numpy # required for HTSeq, a dependency of circtools
pip install git+https://github.com/jakobilab/circtools.gitThe primer-design module as well as the exon analysis and circRNA testing module
require a working installation ofRwithBioConductor. All R packages
required can be automatically installed during the setup. Please see the“Installing circtools”chapter of the main circtools documentation for more detailed installation instructions.ModulesCirctools currently offers seven modules:detect(detailed documentation)Thedetectcommand is an interface toDCC, developed at the
Dieterich Lab. The module allows to detect circRNAs from RNA sequencing
data. The module is the foundation of all other steps for the circtools
work flow. All parameters supplied to circtools will be directly passed
to DCC.quickcheck(detailed documentation)The quickcheck module of circtools is an easy way to check the results
of a DCC run for problems and to quickly assess the number of circRNAs
in a given experiment. The module needs the mapping log files produced
by STAR as well as the directory with the DCC results. The module than
generates a series of figures in PDF format to assess the results.reconstruct(detailed documentation)Thereconstructcommand is an interface toFUCHS. FUCHS is employing
DCC-generated data to reconstruct circRNA structures. All parameters
supplied to circtools will be directly passed to FUCHS.circtest(detailed documentation)Thecirctestcommand is an interface toCircTest. The module a a
very convenient way to employ statistical testing to circRNA candidates
generated with DCC without having to write an R script for each new
experiment. For detailed information on the implementation itself take a
look at theCircTest
documentation. In
essence, the module allows dynamic grouping of the columns (samples) in
the DCC data.exon(detailed documentation)The exon module of circtools employs theballgown R
packageto combine data generated with DCC and circtest with ballgown-compatiblestringtieoutput or cufflinks output converted viatablemakerin order get
deeper insights into differential exon usage within circRNA candidates.enrich(detailed documentation)Theenrichmentmodule may be used to identify circRNAs enriched for
specific RNA binding proteins (RBP) based on DCC-identified circRNAs and
processedeCLIPdata. For K526 and HepG2 cell lines plenty of this data is available
through theENCODEproject.primer(detailed documentation)Theprimercommand is used to design and visualize primers required
for follow up wet lab experiments to verify circRNA candidates.