find_circ protocols

View find_circ computational protocol

find_circ statistics

To access cutting-edge analytics on consensus tools, life science contexts and associated fields, you will need to subscribe to our premium service.


Citations per year

Citations chart

Popular tool citations

chevron_left Circular RNA detection chevron_right
Popular tools chart

Tool usage distribution map

Tool usage distribution map

Associated diseases

Associated diseases

find_circ specifications


Unique identifier OMICS_10928
Name find_circ
Software type Application/Script
Interface Command line interface
Restrictions to use Academic or non-commercial use
Input data RNA-seq reads
Output data The detected linear and circular candidate splice sites.
Output format BED
Operating system Unix/Linux
Programming languages Python
License GNU General Public License version 3.0
Computer skills Advanced
Version 1.2
Stability Stable
Numpy, pysam
Maintained Yes


Add your version



  • person_outline Nikolaus Rajewsky <>

Publication for find_circ

find_circ in pipelines

PMCID: 5780853
PMID: 29363420
DOI: 10.1186/s12864-017-4335-9

[…] on purpose of covering as many different conditions as possible. quality control of the sequence reads was conducted through the ngs qc toolkit [] with default setting. the algorithm referred as find_circ [, ] was applied to detect back-splicing junctions. to normalize the amount of the normalized sequence reads spanning the junctions, a concept of spliced reads per billion mapping (srpbm) […]

PMCID: 5940110
PMID: 29723158
DOI: 10.18632/aging.101437

[…] that aligned in the reverse orientation (head-to-tail) indicated that circrna splicing had occurred. the anchor reads were mapped to the tree shrew genome again and the results were submitted to find_circ [] software to identify circrnas., the identified circrnas were subjected to statistical analysis based on their type, chromosome distribution, and length distribution. to quantify […]

PMCID: 5377590
PMID: 28420964
DOI: 10.3389/fnmol.2017.00091

[…] and to eliminate overlapping and coding potential transcription with annotation of database at exon region (cuffcompare software). circrnas were identified base on the data of lncrnas with find_circ (memczak et al., ). clean reads were screened the lengh of 21–22 nt as mirna, and located to reference sequence with bowtie. combined with mirevo software (wen et al., ) and mirdeep2 […]

PMCID: 5471026
PMID: 28415618
DOI: 10.18632/oncotarget.16442

[…] trimmed reads were used for analysis of circrnas. the high quality reads were aligned to the reference genome/transcriptome using bowtie2 software and circrnas were detected and identified using find_circ software [, ]. raw junction reads for all samples were normalized to the number of total mapped reads and log2 transformed. circos software was used to construct the circos figure []. […]

PMCID: 5618626
PMID: 28906455
DOI: 10.3390/ijms18091977

[…] reference genome []. unmapped reads were kept, and 20-mers from 5′ and 3′ ends were extracted and aligned independently to reference sequences by bowtie v2.0.6 []. anchor sequences were extended by find_circ1 such that they were completely read-aligned, and the breakpoints were flanked by gu/ag splice sites. backspliced reads with at least two supporting reads were then annotated as circrnas. […]

To access a full list of citations, you will need to upgrade to our premium service.

find_circ in publications

PMCID: 5946474
PMID: 29747577
DOI: 10.1186/s12864-018-4754-2

[…] directly. bowtie (v2.0.6) [] was used to build index of the reference genome, and tophat (v2.0.9) [] was used to align paired-end clean reads to the reference genome. in addition, the software find_circ [] was used to extend the anchor sequences and the back-spliced reads containing at least two supporting reads were considered to be circrnas., the softwares scripture beta2 [] […]

PMCID: 5941680
PMID: 29739336
DOI: 10.1186/s12864-018-4670-5

[…] microdissected from the posterior cingulate (pc) of alzheimer’s disease (ad) patients (n = 10) and healthy elderly controls (n = 10) using four circrna prediction algorithms - ciri, circexplorer, find_circ and knife., overall, utilizing these four tools, we identified a union of 4438 unique circrnas across all samples, of which 70.3% were derived from exonic regions. notably, the widely […]

PMCID: 5954272
PMID: 29764361
DOI: 10.1186/s12864-018-4456-9

[…] read archive (sra). the back-spliced junction sites in each rna-seq sample were identified using a circrna discovery pipeline adapting the scripts provided on circbase [, ], which was referred as find_circ []. detected back-spliced junction sites, along with the collected junction sites from previous reports, were further compared with the hg19 human genome annotation from refseq to annotate […]

PMCID: 5940110
PMID: 29723158
DOI: 10.18632/aging.101437

[…] the mapped rrna reads had been removed were mapped to the tree shrew genome using tophat2, and the unmapped reads were selected. based on theoretical predictions, 35,007 circrnas were detected using find_circ. all of the identified circrnas were novel. as shown in , most of the circrnas were approximately 400 nt in length, as found in previous studies []. in addition, different types of circrnas […]

PMCID: 5928111
PMID: 29713025
DOI: 10.1038/s41598-018-25242-w

[…] rnas were used to construct libraries, which were sequenced by an illumina hiseq. 2500 analyzer. when adaptor sequences and low-quality reads were removed, the clean reads were subjected by find_circ software to identify circrnas. a set of confident back-spliced junction reads including 702 from my_1, 2, 517 from my_2, 2,386 from co_1, and 4,068 from co_2, were obtained for identifying […]

To access a full list of publications, you will need to upgrade to our premium service.

find_circ institution(s)
Systems Biology of Gene Regulatory Elements, Max-Delbruck-Center for Molecular Medicine, Berlin, Germany; Angiogenesis and Cardiovascular Pathology, Max Delbruck-Center for Molecular Medicine, Berlin, Germany; RNA Biology and Post-Transcriptional Regulation, Max-Delbruck-Center for Molecular Medicine, Berlin, Germany; Signaling Dynamics in Single Cells, Max-Delbruck-Center for Molecular Medicine, Berlin, Germany
find_circ funding source(s)
Supported by PhD program of the Max-Delbruck-Center (MDC); the MDC-NYU exchange program; BMBF project 1210182, ‘MiRNAs as therapeutic targets’; DFG for KFO218; Helmholtz Association for the ‘MDC Systems Biology Network’, MSBN; BMBF support for the DZHK; Center for Stroke Research Berlin and BMBF-funding for the Berlin Institute for Medical Systems Biology (0315362C).

find_circ review

star_border star_border star_border star_border star_border
star star star star star

Rajnish Kumar

star_border star_border star_border star_border star_border
star star star star star
find_circ was first Circular RNAs identification tools which was open source available. This is very simple to use and implement. The whole pipeline is written using python and and it uses python based dependency like NumPy. The code is very simply written which can be simply understood. The most interesting thing is that , it start with unmapped reads , which are considered to be unmapped because these reads supposed to cross the splice junctions. The tool make pseudo pair-end by taking the end fragments of unmapped reads of some size (e.g. 20). The newly constructed pair-end file are mapped using the Bowtie2 tool. Primary mapping of these pairs is discriminated based on their mapping order, means if the sub-reads are mapped following the canonicity principle then its may be potential start target for finding the linear splice sites and if their is any non- canonicity or non-linearity in the order , then it is considered as the starting point of back splice sites. The tool uses one level of filtering at these step by considering only the mapped pair which are on the same chromosome for the further step of identification.In the next step the alignment is extended till it satisfy the constraint given with the tools. Out of many hits best one is selected and reported as linear or back-splice sites based on the using the above mentioned staring target.Beautifully this tool report the average quality of the back-splice sub-reads and number of the reads support the particular sites. To reduce the false positive circular candidates it used the min and max intron size as one of the filtering criteria. The minimum reads supporting the back-splice site was taken as 2 , which can be high for better stringency criteria. Overall the tool is user friendly and useful for prediction study.