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sgRNA Scorer specifications

Information


Unique identifier OMICS_15503
Name sgRNA Scorer
Interface Web user interface
Restrictions to use None
Input data The genomic sequence, user's email address, the CRISPR system, the spacer length, the PAM sequence and orientation.
Input format FASTA
Output data The guide RNA sequences and scores.
Programming languages Python
Computer skills Basic
Version 2.0
Stability Stable
Maintained Yes

Documentation


Maintainer


  • person_outline Raj Chari

Information


Unique identifier OMICS_15503
Name sgRNA Scorer
Software type Application/Script
Interface Command line interface
Restrictions to use None
Input data The genomic sequence.
Input format FASTA
Output data The guide RNA sequences and scores.
Operating system Unix/Linux, Mac OS
Programming languages Python
Computer skills Advanced
Version 2.0
Stability Stable
Requirements
BioPython, Sci-kit learn
Maintained Yes

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No version available

Documentation


Maintainer


  • person_outline Raj Chari

Publication for sgRNA Scorer

sgRNA Scorer citations

 (6)
library_books

Generation of an arrayed CRISPR Cas9 library targeting epigenetic regulators: from high content screens to in vivo assays

2018
Epigenetics
PMCID: 5810758
PMID: 29327641
DOI: 10.1080/15592294.2017.1395121

[…] On-target efficacy of sgRNAs was predicted in silico using both Rules Set 2 (RS2) from the Azimuth project [], and sgRNA Scorer 2.0 (SS2) [] prediction models using available python scripts [RS2 v1.2 (accessed August 2016), SS2 v2 (accessed May 2017)]. In the case of RS2 only the raw sequence option (--seq) was us […]

library_books

Refined sgRNA efficacy prediction improves large and small scale CRISPR–Cas9 applications

2017
Nucleic Acids Res
PMCID: 5814880
PMID: 29267886
DOI: 10.1093/nar/gkx1268

[…] oss-comparison between the two algorithms (rule set I and II) illustrated the different predicted activities they assigned to our sgRNAs ().We next tested the alternative library-on-library approach, sgRNA Scorer by Chari et al. (), on our dataset. The correlation between our data and the predicted activities from this algorithm did not improve compared to rule set II (), although a trend of high […]

library_books

CRISPR offinder: a CRISPR guide RNA design and off target searching tool for user defined protospacer adjacent motif

2017
PMCID: 5723913
PMID: 29230095
DOI: 10.7150/ijbs.21312

[…] ave expanded the range of genome editing experiments.Since the development of CRISPR technology, a number of CRISPR design tools have been created, such as Cas-OFFinder , sgRNAcas9 , CFD_Scoring and sgRNA.Scorer 2.0 . However, most of these tools can only design sgRNAs for the CRISPR/Cas system. In this study, a user-friendly standalone program named “CRISPR-offinder” was developed to provide res […]

library_books

The lncRNA CASC15 regulates SOX4 expression in RUNX1 rearranged acute leukemia

2017
Mol Cancer
PMCID: 5517805
PMID: 28724437
DOI: 10.1186/s12943-017-0692-x

[…] er element [] to remove an internal BbsI restriction site. The 20-nt gRNA sequences flanking a 3.1–3.8 kb region (encompassing the first two exons) of mouse Casc15 (2610307P16Rik) were designed using sgRNA Scorer with CasFinder []. Detailed methods are available upon request. […]

library_books

Cpf1 nucleases demonstrate robust activity to induce DNA modification by exploiting homology directed repair pathways in mammalian cells

2016
Biol Direct
PMCID: 5024423
PMID: 27630115
DOI: 10.1186/s13062-016-0147-0

[…] ithout employing any prior knowledge of the sequence specificities of the nucleases. This was not the case for SpCas9, where we exploited the existence of gRNA prediction tools: sgRNA designer [] and sgRNA scorer 1.0 [] and accepted targets scoring above either 0.5 or 50, respectively. In case of Cpf1 nucleases, representative targets were picked from the 20 targets used on Fig. . All targets were […]

library_books

Nuclease Target Site Selection for Maximizing On target Activity and Minimizing Off target Effects in Genome Editing

2016
PMCID: 4786925
PMID: 26750397
DOI: 10.1038/mt.2016.1

[…] y. However, although the algorithm was validated with a previous CRISPR knockout library screen in human and mouse cells, it was not tested for designing a gRNA for a given input sequence. Similarly, sgRNA Scorer () ranks gRNAs for high activity based on an algorithm generated using data from gRNAs tested in HEK293T cells. This study noted some correlation between site accessibility and gRNA activ […]


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sgRNA Scorer institution(s)
Department of Genetics, Harvard Medical School, Boston, MA, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, MA, USA
sgRNA Scorer funding source(s)
This work was supported by NIH grant P50 HG005550.

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