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A bioinformatic approach to implementing CRISPR screening studies in colorectal carcinoma
University of Skövde, School of Bioscience.
University of Skövde, School of Bioscience.
2026 (English)Independent thesis Basic level (degree of Bachelor), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) is a novel method of targeted gene modification within the cell's genome using guide RNAs (gRNA). One of CRISPR applications is using single guide RNA (sgRNA) directing the unit to a specific genome location, inhibiting the function of the gene. This mechanism has been used recently in cancer screening, where individual genes can be targeted across defined genomic sites. Due to variations in experimental protocols and sgRNA targeted genes, there is no direct method by which to compare the results across datasets. Hence, in this study, two edgeRbased pipelines were constructed that would allow for direct comparison between two genome-wide CRISPR screening datasets of colorectal carcinoma, the Wellcome Sanger Institute’s (Sanger) and the Broad Institute's DepMap (Achilles) datasets. The Achilles results from edgeR were also compared to Model-based Analysis of Genome-wide CRISPR/Cas9 Knockout (MAGeCK) for comparison and validation of the edgeR results. The pipelines successfully identified overlapping genes across datasets associated with colorectal carcinoma, such as RAS related nuclear protein (RAN) connected to the PI3K/Akt/mTOR and Ras-Raf-MEK-ERK pathways in addition to identifying RDX and MATN2 regulatory genes in both cell lines. From the 787 overlapping genes the majority had a negative cross dataset correlation in logarithmic fold change (LFC), with only 36 genes sharing concordance in LFC. In addition, the Achilles MAGeCK MLE results identified a small number of essential genes, which failed to overlap with the essential genes identified in the edgeR pipeline. 

Place, publisher, year, edition, pages
2026. , p. 32
National Category
Bioinformatics and Computational Biology
Identifiers
URN: urn:nbn:se:his:diva-26876OAI: oai:DiVA.org:his-26876DiVA, id: diva2:2084584
Subject / course
Bioinformatics
Educational program
Molekylär bioinformatik
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Available from: 2026-07-06 Created: 2026-07-06 Last updated: 2026-07-06Bibliographically approved

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2930313233343532 of 292
CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
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  • nn-NB
  • sv-SE
  • Other locale
More languages
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