a web-based designing tool forCytosineBaseEditor mediated geneInactivation
Update time | Log |
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2018-10-28 | Release Crispr-CBEI. |
2018-12-27 | Add localy off-target prediction function. |
2019-08-19 | Rearrange UI,prediction logic and add ORF identification. |
2019-09-01 | The Python version of CrisprCBEI released (autocbei). |
2019-10-27 | Increased support for introns. |
2020-06-30 | "autocbei" supported "pip" and "conda" installations. |
We have prepared a detailed, step-by-step user manual for CBEI design or off-target prediction.
Please download and view.
When ORF detection is performed, you can set whether the input sequence contains introns in "Customize ORF detection". At this point, you can enter the coordinates of the CDS. Separate exons with "," and use ".." to separate the begin and end of exons, as in: 1..102, 216..467
You can search for related genes in NCBI, GeneBank format will mark the location of CDS, and copy it directly. How to set up exons is clearly explained in the user manual.
CRISPR-CBEI supports flexible local off-target prediction,that is,you can select any desired local Fasta file to compare to the spacer sequence chosen! If you used our supplied Demo sequence,the LacZ gene,you could download this test genome sequence, Test.fa ,for off-target prediction.
Select your Fasta file (e.g.,Test.fa),and then select "Mismatch" number(Default: mismatch is less than or equal to 3),click "Start prediction!" ,CRISPR-CBEI will quickly complete the calculation subsequently and display the predicted result. Of course,you can use cDNA,ORF or CDS sequences in Fasta format to make the off-target prediction.
CRISPR-CBEI off-target prediction function is a front-end prediction tool that supports local Fasta format files for off-target prediction without uploading to the server. Through algorithm optimization, CRISPR-CBEI does not limit the size of Fasta files, and the spacer alignment speed is fast. The whole off-target calculation process is asynchronous and does not occupy much memory (about 200MB), so it would not affect other applications of the computer. Computational efficiency depends on the CPU, and the higher the primary frequency, the higher the efficiency. Note that, in our tests, we also found that running other computing tasks on the computer at the same time increased the time consumption.
Test environment: i5-3470 3.20GHz
Species | File size | Mismatch<=3 | Mismatch<=2 | Mismatch<=1 | Mismatch==0 |
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