# Computational Tools and Resources Supporting CRISPR-Cas Experiments
## 5 Outcomes Analysis
The methods described above can be used to analyze editing outcomes at on-target sites as well as at the off-target sites predicted in silico. This approach is, however, biased towards the predicted sites, and, usually, only the most probable cleavage sites are actually assayed. This, consequently, poses the risk of omitting the unpredicted or low-likely cleavages. The solution for this issue is to apply whole-genome sequencing (WGS) but the technique is expensive and unsuitable for analysis of many clones, additionally, it requires high coverage to detect low-frequency edits. All these problems resulted in the development of a distinct group of methods dedicated to cleavage detection across the entire genome without the requirement for WGS data. This group consists of techniques used to identify DSBs generated in living cells and in cell-free in vitro systems. The first type of methods includes unbiased identification of double-strand breaks evaluated by sequencing (GUIDE-seq), High-Throughput, Genome-wide translocation Sequencing (HTGTS), Integration-Deficient Lentiviral Vector (IDLV), direct in situ Breaks Labeling, Enrichment on Streptavidin, and next-generation Sequencing (BLESS) and Discovery of In Situ Cas Off-targets and VERification by sequencing (DISCOVER-seq) [12,98,99,100,101]. The second type consists of Selective enrichment and Identification of Tagged genomic DNA Ends by sequencing (SITE-Seq) and Circularization for In vitro Reporting of CLEavage Effects by sequencing (CIRCLE-seq) [69,102]. The latter group has the advantage of eliminating the necessity for cell culture and transfection of cells with components of the CRISPR-Cas system. In spite of different technical approaches, all these methods rely eventually on NGS sequencing. Some of these techniques are supplemented with dedicated computational pipelines facilitating the data analysis such as BLENDER (BLunt End finder) used for identification of off-target edits sites by ChIP-Seq in DISCOVER-seq method [101]. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Compared Feature** & **CRISPRResso2** & **Cas-Analyzer** & **CRISPR-GA** & **TIDE/TIDER** \\ \hline Type of analysis & NGS & NGS & NGS & Sanger sequencing \\ File type & FASTQ & FASTQ & FASTQ & ABI \\  & -inded sizes & & & \\  & and positions & -indel sizes & -indel sizes & -indel sizes \\ Output & -sequence alignment & -HDR/NHEI frequency & -HDR/NHEI & and positions \\  & with reference & -sequence alignment & -HDR/NHEI & -HDR/NHEI frequency \\  & -allele specific & with reference & frequency & \\  & quantification & & & \\ Batch functionality & YES & NO & NO & NO \\ Base editing & YES & NO & NO & NO \\ experiments & Template-mediated & YES & YES & YES (TIDER) \\ editing & & SpCas9, gTcSa9, & & \\  & & NmCas9, SaCas9, & & SpCas9, SaCas9, \\  & & JCCas9, AsCpf1/1 DCpPf1, & & StCas9, NmCas9, \\  & & paired nucleases, & Cas9 & AsCpf1, FnCpf1, \\  & & ZPNs, TALENS, Cas9 & & LBCpPf1 \\  & & nickases, dCas9-FokI & & \\ Need to upload dataset & YES & (up to 100 Mb) & NO & YES & YES \\  & & & & \\ command line interface & YES & NO & NO & NO \\  & & & & \\  & References & [90] & [88] & [89] & [49,92] \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of web-based postexperimental analysis tools.