Compare · 4 tools
CRISPR analysis tools you can run online
These tools detect natural CRISPR arrays and Cas genes in genomic sequences, design human SpCas9 guide RNAs, and identify essential genes from genome-scale knockout screens.
What crispr analysis tools do
CRISPR computational tools support different phases of study, spanning the discovery of natural immune systems in microbial genomes to the design and interpretation of Cas9 laboratory experiments. For genome mining, tools search nucleotide sequences to detect repeat-spacer arrays and map CRISPR-associated (Cas) gene systems in isolate genomes or environmental contigs.
For experimental applications, methods address guide selection and phenotypic screening. Computational models evaluate candidate guide RNAs by predicting on-target cutting efficiency and potential off-target cleavage across the genome, while screen analysis pipelines take read count matrices from pooled knockout screens to identify which target genes are functionally critical.
Compared
- MinCEDCRISPRIdentifies CRISPR arrays in complete genomes and assembled metagenomic contigs.See its pageOn demand
- CRISPRCasFinderCRISPRIdentifies CRISPR arrays and neighbouring Cas genes in genome sequences for researchers.See its pageOn demand
- DeepCRISPRCRISPRPredicts SpCas9 sgRNA on-target knockout efficacy and off-target cleavage profiles in human genomic sequences.See its pageOn demand
- MAGeCKCRISPRIdentifies functionally important genes from genome-scale CRISPR-Cas9 knockout screens using sgRNA read counts.See its pagePreinstalled
How to choose
To detect naturally occurring CRISPR elements in genomic sequences, choose between MinCED and CRISPRCasFinder based on whether Cas protein annotation is required. MinCED identifies CRISPR repeat-spacer arrays in complete genomes and assembled metagenomic contigs, outputting both tabular summaries and GFF files with user-adjustable repeat thresholds. CRISPRCasFinder identifies CRISPR arrays and also uses MacSyFinder and CASFinder models to detect neighbouring Cas genes.
For laboratory experiments involving SpCas9, the choice depends on whether the task is guide RNA design or screen interpretation. DeepCRISPR designs single guide RNAs for human targets with NGG PAMs, generating predictions for on-target knockout efficacy and off-target cleavage profiles. MAGeCK is used downstream of screens to process sgRNA read count tables from genome-scale CRISPR-Cas9 knockout experiments, ranking significant genes with low false discovery rates and providing built-in visualisation utilities.
Technical dependencies and input formats also separate these tools. MinCED accepts FASTA files and runs as a Java command-line utility, though it is not intended for raw short reads in the 100–200 bp range. CRISPRCasFinder accepts FASTA sequences and operates as a Perl pipeline or Singularity container, requiring external tools including Vmatch and MacSyFinder as well as Perl modules like Date::Calc. DeepCRISPR runs on legacy Python 3.6, TensorFlow 1.3.0, and Sonnet 1.9 environments, requiring 8-channel input with ENCODE epigenetic features for off-target cleavage scoring, whereas MAGeCK is implemented in C and Python to handle tabular count matrices.
Questions
Can I run these tools without a GPU or installing anything?
Yes. The research agent runs each of these on a machine of its own — some are preinstalled, others are set up the first time a task needs them — and reads the results back to you.
Which tool can identify Cas genes alongside CRISPR arrays?
CRISPRCasFinder identifies both CRISPR arrays and neighbouring Cas genes using MacSyFinder and CASFinder models. MinCED identifies CRISPR arrays but does not identify Cas genes.
Can MinCED process raw, unassembled short reads?
No. MinCED is designed for complete isolate genomes and assembled metagenomic contigs, and is not intended for raw short reads in the 100–200 bp range.
Can DeepCRISPR predict off-target cleavage using sequence data alone?
No. DeepCRISPR offers a 4-channel sequence-only model solely for on-target efficacy scoring. Predicting off-target cleavage requires the full 8-channel input incorporating cell-type-specific epigenetic features from ENCODE.
What input does MAGeCK require?
MAGeCK takes sgRNA read count tables generated from genome-scale CRISPR-Cas9 knockout screens as its input to evaluate guide performance and rank target genes.
Written from each tool's own documentation, as summarised on its page here. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.