CRISPResso processing
Generated by: George Chlipala
Report date: July 8, 2026
Overview
When you publish manuscripts based on data generated at our facility, we would greatly appreciate an acknowledgement of our efforts. Please cite our facility as follows (for example):
Basic processing of the raw data were performed by the University of Illinois at Chicago Research Informatics Core (UICRIC).
We adhere to a general policy for acknowledgements and authorship as established by the Association for Biomolecular Resource Facilities (ABRF) , and we support the following statement from the ABRF.
The existence of core facilities depends in part on proper acknowledgment in publications. This is an important metric of the value of most core facilities. Proper acknowledgment of core facilities enables them to obtain financial and other support so that they may continue to provide their essential services in the best ways possible. It also helps core personnel to advance in their careers, adding to the overall health of the core facility.
Please contact us for assistance in drafting manuscripts.
| File | Description | Type |
|---|---|---|
| CRISPRessoBatch_on_crispresso_batch.html | CRISPResso report | result |
| Sample | OriginalID |
|---|---|
| Sample001 | Sample001 |
| Sample002 | Sample002 |
| Sample003 | Sample003 |
| Sample004 | Sample004 |
| Sample005 | Sample005 |
| Sample006 | Sample006 |
| Sample007 | Sample007 |
| Sample008 | Sample008 |
| Sample009 | Sample009 |
| Sample010 | Sample010 |
- Method: cutadaptMartin, M. (2011). Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal, 17(1):10-12. doi:https://doi.org/10.14806/ej.17.1.200 (version: 4.4)
-
Custom ParametersSequencing trimming using cutadapt - -a = AGACCAAGTCTCTGCTACCGTA
- -A = TGTAGAACCATGTCGTCAGTGT
- --report = minimal
- -m = 50
- Method: Quality trimming
-
Custom ParametersQuality trimming based on quality threshold and length parameters. - min length = 50
- Method: Adapter trimming
-
Custom ParametersAdapter/primer sequences were trimmed from the reads. - 5' adapter = AGACCAAGTCTCTGCTACCGTA
- 5' adapter (read2) = TGTAGAACCATGTCGTCAGTGT
Figure 1 . Trimming results
Table 1 . Trimming statistics
| Sample | Trim passed | Ambig dropped | Trim filter dropped | Trim length dropped | Percent passed | Mean Length | Mean Trimmed Length | Quality trimmed bp |
|---|---|---|---|---|---|---|---|---|
| Sample001 | 14881 | 0 | 0 | 10 | 99.93% | 306.0 | 305.6 | 0 |
| Sample002 | 12102 | 0 | 0 | 5 | 99.96% | 306.0 | 305.6 | 0 |
| Sample003 | 10792 | 0 | 0 | 21 | 99.81% | 306.0 | 305.6 | 0 |
| Sample004 | 12120 | 0 | 0 | 7 | 99.94% | 306.0 | 305.7 | 0 |
| Sample005 | 12452 | 0 | 0 | 9 | 99.93% | 306.0 | 305.0 | 0 |
| Sample006 | 12317 | 0 | 0 | 9 | 99.93% | 306.0 | 305.1 | 0 |
| Sample007 | 9308 | 0 | 0 | 13 | 99.86% | 306.0 | 305.9 | 0 |
| Sample008 | 7667 | 0 | 0 | 28 | 99.64% | 306.0 | 305.9 | 0 |
| Sample009 | 9070 | 0 | 0 | 6 | 99.93% | 306.0 | 305.9 | 0 |
| Sample010 | 6422 | 0 | 0 | 2956 | 68.48% | 306.0 | 305.2 | 0 |
- Method: CRISPResso 2Clement K, Rees H, Canver MC, Gehrke JM, Farouni R, Hsu JY, Cole MA, Liu DR, Joung JK, Bauer DE, Pinello L. CRISPResso2 provides accurate and rapid genome editing sequence analysis. Nat Biotechnol. 2019 Mar; 37(3):224-226. doi: 10.1038/s41587-019-0032-3. PubMed PMID: 30809026.
-
Custom ParametersAnalysis of genome editing outcomes from deep sequencing data - amplicon_sequence = TAAACTACCAGAAGTATCAGTGCTAAAAGTATCCTTTTCTTTCCTACAGATTCCTCCTTATGGCCAACAAGGCCCCAGCGGGTATGGTCAGCAGGGCCAGACTCCATATTACAACCAGCAAAGTCCTCACCCCCAGCAGCAGCAGCCACCCTACTCTCAGCAACCACCATCCCAGACCCCTCATGCTCAACCTTCATATCAGCAGCAGCCTCAGTCTCAGCCACCACAGCTCCAGTCATCTCAGCCTCCATATTCCCAGCAGCCA
- sgRNA = GGACTTTGCTGGTTGTAATA
Figure 1 . Overview of mapping statistics
Figure 2 . Overview of quantification
Table 1 . Mapping statistics
| Sample | READS IN INPUTS | READS AFTER PREPROCESSING | READS ALIGNED | N_COMPUTED_ALN | N_CACHED_ALN | N_COMPUTED_NOTALN | N_CACHED_NOTALN |
|---|---|---|---|---|---|---|---|
| Sample001 | 14881 | 14518 | 14424 | 1609 | 12815 | 29 | 65 |
| Sample002 | 12102 | 11721 | 11583 | 3187 | 8396 | 62 | 76 |
| Sample003 | 10792 | 10456 | 10360 | 2845 | 7515 | 42 | 54 |
| Sample004 | 12120 | 11903 | 11848 | 1404 | 10444 | 13 | 42 |
| Sample005 | 12452 | 12063 | 11785 | 3064 | 8721 | 105 | 173 |
| Sample006 | 12317 | 11880 | 11619 | 3342 | 8277 | 100 | 161 |
| Sample007 | 9308 | 9138 | 9101 | 1176 | 7925 | 15 | 22 |
| Sample008 | 7667 | 7439 | 7374 | 886 | 6488 | 36 | 29 |
| Sample009 | 9070 | 8830 | 8789 | 1154 | 7635 | 24 | 17 |
| Sample010 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Table 2 . Quantification statistics
| Sample | UNMODIFIED | MODIFIED | AMBIGUOUS | Percent UNMODIFIED | Percent MODIFIED | Percent AMBIGUOUS |
|---|---|---|---|---|---|---|
| Sample001 | 14332 | 92 | 0 | 99.4 % | 0.638 % | 0 % |
| Sample002 | 3844 | 7739 | 0 | 33.2 % | 66.8 % | 0 % |
| Sample003 | 3374 | 6986 | 0 | 32.6 % | 67.4 % | 0 % |
| Sample004 | 11784 | 64 | 0 | 99.5 % | 0.54 % | 0 % |
| Sample005 | 4723 | 7062 | 0 | 40.1 % | 59.9 % | 0 % |
| Sample006 | 4411 | 7208 | 0 | 38 % | 62 % | 0 % |
| Sample007 | 50 | 9051 | 0 | 0.549 % | 99.5 % | 0 % |
| Sample008 | 7 | 7367 | 0 | 0.0949 % | 99.9 % | 0 % |
| Sample009 | 1 | 8788 | 0 | 0.0114 % | 100 % | 0 % |