The CRISPR Comparison Toolkit (CCTK) is now published in @CRISPRjournal with @RachelJWhitaker! Github Conda Read the docs 1/3.

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Thank you to reviewers and users who submitted bug reports for helping to improve CCTK over the last year! We hope to continue to improve it moving forward!.3/3.

See the thread associated with the preprint for a description of what CCTK can do and check out the releases page to see the new features and bug fixes since CCTK was first released almost a year ago. 2/3.

We hope that CCTK will be useful for your research! CCTK can be installed via conda (, source code is available on GitHub (, and documentation is available on RTD ( 15/15.

You can visualize how many targets each spacer has (or other data), by using custom colour schemes for CCTK tools. Here is the CRISPRdiff plot with spacers coloured according to the number of targets we found. 14/15

Spacerblast can identify targets with mismatches by extending truncated BLAST hits and can search for PAMs defined using either IUPAC nucleotide codes or regex. It can also mask regions from the search. 13/15.

Identification of matches can be done using BLAST. However it is laborious for large numbers of spacers or matches. We therefore included Spacerblast in CCTK, which is a BLASTn wrapper with a few extra steps. 12/15.

Finally, CRISPR systems are adaptive immune systems that provide protection via sequence-specific targeting MGEs. Targets can be identified by finding sequence matches to spacers where the matches are flanked by a motif called a PAM. 11/15.

Constrain infers how arrays may evolved if their history were *constrained* by a certain topology. In the case of these arrays, Constrain indicates that horizontal gene transfer may have occurred (indicated by red boxes). 10/15

The tree inferred by CRISPRtree represents a hypothesis of the history of these arrays. However, the CRISPRtree tree differs from a tree based on a core genome alignment. The tool Constrain can be used to explore this difference. 9/15.

Looking at the CRISPRdiff plot, you can see that some arrays are very similar, and some are more distinct. CRISPRtree can infer a maximum parsimony tree to describe those relationships. It also produces a hypothesis of how the arrays evolved. 8/15

There are other great tools for visualizing CRISPR arrays: CRISPRViz ( and CRISPRStudio (. We discuss key differences in the manuscript. 7/15.

Each cluster of homologous arrays can then be explored in more detail. First, which parts of each array are shared with, or distinct from, other arrays in the cluster? This is the CRISPRdiff visualization of the largest cluster. 6/15

CCTK represents array homology using a network in which arrays (nodes) are connected by an edge if they have more than 1 identical spacer in common. Edge weight reflects the degree of array similarity. 5/15

CCTK includes two utilities to identify CRISPR arrays. One uses MinCED ( and the other uses BLASTn. CCTK then orients the arrays relative to the leader end and identifies homologous clusters of arrays. 4/15.

CCTK is therefore designed to identify CRISPR arrays in large numbers (100s to 1000s) of assemblies. CCTK then allows you to explore groups of arrays in more detail to visualize arrays and to infer their evolutionary history. 3/15.

CCTK was born out of a desire to analyze CRISPR arrays from large numbers of isolates. We wanted to know which arrays were homologous to one another (i.e., contain the same spacers), but also the nature of their relationships. 2/15.

I’m excited to announce a new preprint with @RachelJWhitaker! We developed a command line toolkit for the identification and analysis of CRISPR arrays, called the CRISPR Comparison ToolKit (CCTK). A thread about what it can be used for: 1/15.

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