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Pipeline publication

[…] hways (). The presence of these insertions underscores the need to consider plasmid-free Cas9 delivery in hPSCs, such as RNPs, that may reduce the potential integration of unwanted sequences with high or degenerate homology to sequences adjacent to the DSB., Next-generation sequencing is a powerful tool to identify indels generated by gene targeting, however, downstream analytical pipelines often use different alignment methodologies, threshold criteria, and variant effect predictors, which can substantially influence outcomes (). To further validate our findings, we developed a sequence-evaluation tool, which we called BaySnpper (A; https://github.com/dat4git/BaySnpper). BaySnpper utilized FreeBayes (FB) () to create composite calls from forward and reverse sequence reads and SnpEff to make predictions about the indel effect (). Data were exported to generate Tab Separated Values (TSV) files as well as annotated Variant Call Format (VCF) files for visualization in Integrative Genomics Viewer () or other genome browsers (A). We then re-analyzed 30 individual gene-targeting experiments using BaySnpper and compared calls with those obtained via OutKnocker (A, 5B, and B). As shown in A, indel distribution was similar across 30 genes using data analyzed by OutKnocker and BaySnpper. Both OutKnocker and BaySnpper called an average of approximately 19–22 HET/MIXED clones, 6–7 NULL clones, and 6–8 IN FRAME clones per gene. On a gene-by-gene basis, we also observed similar proportions of HET/MIXED, NULL, and IN FRAME clones (B). It is important to note that clone-to-clone differences did arise, presumably due to differences in alignment algorithms, read thresho […]

Pipeline specifications

Software tools FreeBayes, SnpEff, IGV
Organisms Homo sapiens