TIDER: Easy quantification of template-directed CRISPR/Cas9 editing

Purpose

  • What it does: Estimates the frequency of designed (templated) small mutations in a pool of cells transfected with [Cas9 + sgRNA + template oligonucleotide]. It also determines the frequency of non-templated indels.
  • When to use: Quantification of oligonucleotide-templated point mutations and small indels. For non-templated CRISPR/Cas9, use the original TIDE or TIDE batch web tools.
  • What it needs: Three standard capillary sequencing reactions.
  • Drawbacks: Requires some additional wet-lab work to generate a template reference sequence (see Protocol tab).
  • Reference (please cite!): Brinkman et al, Nucl. Acids Res. (2018).

Overview

TIDER provides rapid and reliable assessment of template-mediate genome editing. It quantifies the efficiency of homology-directed repair ("HDR") in an edited sample by decomposing the sequence trace data from three simple Sanger reactions.

The input to TIDER is Sanger sequencing data.

The output of TIDER is a comprehensive profile of all insertions and deletions (indels) in the edited sample and the frequency of the desired reference (or template) sequence.


sequence trace

License, terms of use and privacy

The TIDE Software is being provided as a free web service for research, educational, instructional and non-commercial purposes only. This webtool and the associated R code are open source software under GNU General Public License version 3. Your uploaded data are only used for the duration of the analysis session and are not stored or used for any other purpose.

All copyright is exclusively owned by Stichting het Nederlands Kanker Insituut - Antoni van Leeuwenhoek ziekenhuis (The Netherlands Cancere Institute). The availability and use of this software is subject to a license from the copyright holder. If you use this software for data analysis in a publication, please cite (Brinkman et al, Nucl. Acids Res. (2018)).

Code

R code of the TIDER can be provided upon request. Contact the Bas van Steensel lab.

Contact

This web tool was developed by Eva Brinkman, Christ Leemans and Bas van Steensel from the Bas van Steensel lab.
For more information and to report bugs, please contact support@datacurators.nl

Acknowledgements

R

R Core Team (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. www.R-project.org . R version 3.1.1.

Biostrings

H. Pages, P. Aboyoun, R. Gentleman and S. DebRoy. Biostrings: String objects representing biological sequences, and matching algorithms. R package version 2.32.1.

sangerseqR

J.T. Hill and B. Demarest (2014). sangerseqR: Tools for Sanger Sequencing Data in R. R package version 1.3.1. http://www.bioconductor.org/packages/devel/bioc/html/sangerseqR.html

nnls

K. M. Mullen and I. H. M. van Stokkum. The Lawson-Hanson algorithm for non-negative least squares (NNLS). R package version 1.4.

msa

E. Bonatesta, C. Horejs-Kainrath, and U. Bodenhofer. Multiple Sequence Alignment. R package version 1.6.0.

plyr

H. Wickham. Tools for Splitting, Applying and Combining Data. R package version 1.8.4.

shiny

RStudio and Inc. (2013). shiny: Web Application Framework for R. R package version 1.0.0. http://shiny.rstudio.com