Code for
François Kroll, Joshua Donnelly, Joshua Donnelly, Güliz Gürel Özcan, Eirinn Mackay, Jason Rihel
Behavioural pharmacology predicts disrupted signalling pathways and candidate therapeutics from zebrafish mutants of Alzheimer’s disease risk genes
eLife, 2024.
https://doi.org/10.7554/eLife.96839.1
The work is associated with two other GitHub repos:
- FramebyFrame R package
- ZOLTAR app. The app in action is at ZOLTAR.
Data is found at Zenodo repository. The present GitHub repo only contains code.
Get in touch for questions
A rough index to help you find the code you want:
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210413_psen1LONGTRACK: experiment in Fig. 2b
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210913_PSEN1, 210907_PSEN2, 220524_APPAB: behaviour experiments in Fig. 3 and supplementary.
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220313_APOEAB_2, 220516_APOEAB_3, 220725_CD2AP, 220601_CLU, 220531_SORL1: behaviour experiments in Fig. 4 and supplementary.
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october2021_MiSeq, 220524_miseq, 220915_miseq: MiSeq sequencing data, as e.g. Fig. 3c.
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221123_PSENab: Aβ measurements in psen1/psen2 knockouts, Fig. 3e.
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230214_sorl1Citalopram: behaviour experiment in Fig. 5 and supplementary.
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230314_psen2Rescue: behaviour experiment in Fig. 6 and supplementary.
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ADgenesHCR: HCRs presented in Fig. 1–suppl. 3 & Fig. 1–suppl. 4.
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FbyFcomparison: plots Fig. 2–suppl. 2b,c.
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fingerprints: most fingerprint plots, as in Fig. 3h.
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geneSelect: donut plot in Fig. 1a.
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transcriptMaps: map of genes as e.g. Fig. 3c.
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utilities: two lost scripts used in different folders. ggFrameshift.R to generate plots of mutated/frameshifted MiSeq reads, as e.g. Fig. 3c. percEffectSize.R to calculate effect sizes of behavioural parameters reported in text.
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zfBrain_scRNAseq: Fig. 1b,c & Fig. 1–suppl. 1 & Fig. 1–suppl. 2; using the single-cell RNA sequencing dataset from Raj et al. 2020.
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zoltarAll: relates to Author Response. Explores results from running ZOLTAR on every F0 knockout tested.