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find_circ specifications

Information


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
Requirements
Numpy, pysam
Maintained Yes

Versioning


No version available

Documentation


Maintainer


  • person_outline Nikolaus Rajewsky

Publication for find_circ

find_circ citations

 (43)
library_books

Genome wide analysis of differentially expressed profiles of mRNAs, lncRNAs and circRNAs during Cryptosporidium baileyi infection

2018
BMC Genomics
PMCID: 5946474
PMID: 29747577
DOI: 10.1186/s12864-018-4754-2

[…] ebsite 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. […]

library_books

Circular RNA expression and regulatory network prediction in posterior cingulate astrocytes in elderly subjects

2018
BMC Genomics
PMCID: 5941680
PMID: 29739336
DOI: 10.1186/s12864-018-4670-5

[…] served that the overlap among the circRNAs detected by the different tools was low. Overall, 243 circRNAs were predicted by all four tools, while each tool also predicted unique circRNAs (KNIFE—1680, find_circ—1077, CIRI—488, CIRCexplorer—198; Fig. ). Most of the candidates called by all the tools originated from CDS (242/243; 99.5%) as well as intronic regions (232/243; 95.5%), and 75% of the exo […]

library_books

Ouroboros resembling competitive endogenous loop (ORCEL) in circular RNAs revealed through transcriptome sequencing dataset analysis

2018
BMC Genomics
PMCID: 5954272
PMID: 29764361
DOI: 10.1186/s12864-018-4456-9

[…] eports in which the back spliced junction sites were reported.The amount of samples among the 465 collected samples in which the back spliced junction sites were found meeting the criteria defined in find_circ [, , ].Only the circRNAs with the combined amount of these two values over 10 were considered in the analysis of this report. […]

library_books

CircRNAs in the tree shrew (Tupaia belangeri) brain during postnatal development and aging

2018
PMCID: 5940110
PMID: 29723158
DOI: 10.18632/aging.101437

[…] eads 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 circRNAs, b […]

library_books

Genome wide Identification and characterization of circular RNAs in the rice blast fungus Magnaporthe oryzae

2018
Sci Rep
PMCID: 5928111
PMID: 29713025
DOI: 10.1038/s41598-018-25242-w

[…] re kept, and 20-mers sequences from 5′ and 3′ end of these reads were used to align reference genome again, by using a software Bowtie v2.0.6. The anchored sequences were subsequently analyzed by the find_circ software, then the complete reads can be aligned with breakpoints flanked by GU/AG splice sites. At last, back-spliced reads with more than two supporting reads were identified as circRNAs. […]

library_books

Improved circRNA Identification by Combining Prediction Algorithms

2018
PMCID: 5844931
PMID: 29556495
DOI: 10.3389/fcell.2018.00020

[…] = (iTPxiTN)∧2) that scores the achieved benefit of pairing one algorithm with any other algorithm (Figure ), e.g., the effect of pairing CIRI with ACSF is 0.27. Based on this it is evident that CIRI, find_circ, and Uroborus profit the most from combination with almost any other algorithm, while MapSplice seems to be the preferred complement to most algorithms. In addition, CIRI2, MapSplice, and th […]

Citations

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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

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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.