Offline version download:

In our offline version, we support batch input of whole genome sequences. And in addition to providing sgRNA performance predictions, we also integrated the Cas-OFFinder tool to output off-target predictions.

Click here to download the CRISPRlnc offline version.

In addition to providing offline downloads, we also provide downloads of nine reference genomes and downloads for CRISPRko and CRISPRi validity sgRNA prediction models

Reference Genome and Prediction Results download

Homo sapiens : GRCH38-Reference Genome;Prediction Results

Mus musculus : GRCm39-Reference Genome;Prediction Results

Danio rerio : GRCz11-Reference Genome;Prediction Results

Drosophila melanogaster : BDGP6.32-Reference Genome;Prediction Results

Gorilla : gorGor4-Reference Genome;Prediction Results

Macaque : Mmul_10-Reference Genome;Prediction Results

Pan paniscus : panpan1.1-Reference Genome;Prediction Results

Capra hircus : ARS1-Reference Genome;Prediction Results

Bos taurus : ARS-UCD1.2-Reference Genome;Prediction Results

Prediction model download

Here we provide the sgRNA models we trained and the corresponding sgRNA training and testing matrices for download, which you can call in your own Python code. Click here to download the CRISPRko and CRISPRi models, and the training and independent testing data matrices.

Our data comes from the following three articles, among which, the CRISPRlnc database provides us with formatted data :

[1] Zhu, S., Li, W., Liu, J. et al(2016). Genome-scale deletion screening of human long non-coding RNAs using a paired-guide RNA CRISPR–Cas9 library. Nat Biotechnol 34, 1279–1286.

[2] Kampmann M. (2018). CRISPRi and CRISPRa Screens in Mammalian Cells for Precision Biology and Medicine. ACS chemical biology, 13(2), 406–416.

[3] Chen, W., Zhang, G., Li, J., Zhang, X., Huang, S., Xiang, S., Hu, X., & Liu, C. (2019). CRISPRlnc: a manually curated database of validated sgRNAs for lncRNAs. Nucleic acids research, 47(D1), D63–D68.