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Python-based automation of INDIGO webserver using Selenium: A high throughput analysis of Sanger sequence data to detect allelic variations created by CRISPR/Cas9-mediated genome editing of crop plants

Suresh, V.; Girish, C.; Tavva, V. S. S.

2025-08-05 bioinformatics
10.1101/2025.08.04.668409 bioRxiv
Show abstract

CRISPR-Cas9 has revolutionized plant genome editing by enabling precise introduction of insertion/deletion (indel) mutations, critical for functional genomics and crop improvement studies. Sanger sequencing, combined with bioinformatics tools like the INDIGO webserver from Gear Genomics, is essential for validating these mutations. However, manual analysis of large numbers of Sanger sequencing (.ab1) files is labor-intensive, particularly when analyzing multiple guide RNA (gRNA) target regions. We developed a Python-based automation pipeline using Selenium with integrated highlighting of protospacer adjacent motif (PAM) regions in the resulting HTML reports. This pipeline enhances scalability of Sanger sequence data analysis and improves result interpretability by automating PAM region identification and supporting multiple gRNA regions. This tool significantly accelerates CRISPR-Cas9-mediated mutation analysis, offering a high throughput, reproducible solution for genome editing research.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Plant Methods
○ 42 papers in training set
Top 0.1%
18.6%
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2
Frontiers in Plant Science
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3
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7
BMC Genomics
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Top 1%
4.3%
50% of probability mass above
8
Plant Direct
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Top 0.8%
4.1%
9
Scientific Reports
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Top 32%
3.2%
10
GigaScience
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Top 1%
2.8%
11
The Plant Genome
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Top 0.4%
2.4%
12
NAR Genomics and Bioinformatics
◐ 242 papers in training set
Top 2%
2.1%
13
Journal of Bioinformatics and Systems Biology
○ 15 papers in training set
Top 0.1%
2.1%
14
Plant Physiology
◐ 238 papers in training set
Top 2%
1.9%
15
PeerJ
◐ 308 papers in training set
Top 5%
1.9%
16
Bioinformatics Advances
◐ 203 papers in training set
Top 3%
1.7%
17
Molecular Ecology Resources
○ 171 papers in training set
Top 1%
1.5%
18
Genes
○ 144 papers in training set
Top 3%
1.1%
19
Frontiers in Genetics
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Top 4%
1.1%
20
Horticulture Research
◐ 47 papers in training set
Top 0.7%
1.1%
21
Briefings in Bioinformatics
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Top 6%
1.1%
22
The CRISPR Journal
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Top 0.4%
0.9%
23
BMC Research Notes
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Top 1%
0.8%
24
Nucleic Acids Research
◐ 1281 papers in training set
Top 13%
0.8%
25
International Journal of Molecular Sciences
○ 494 papers in training set
Top 17%
0.6%
26
F1000Research
○ 88 papers in training set
Top 4%
0.6%
27
Plants
○ 43 papers in training set
Top 2%
0.6%
28
The Plant Journal
○ 215 papers in training set
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29
G3 Genes|Genomes|Genetics
◐ 351 papers in training set
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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.