Analysis of bulk RNAseq data, differential expression using LME.
This R project contains the code to generate Figures for the publication titled: Transcriptional signature of islet neogenesis-associated protein peptide-treated rat pancreatic islets reveals induction of novel long non-coding RNAs URL: https://www.frontiersin.org/articles/10.3389/fendo.2023.1226615/full?&utm_source=Email_to_authors_&utm_medium=Email&utm_content=T1_11.5e1_author&utm_campaign=Email_publication&field=&journalName=Frontiers_in_Endocrinology&id=1226615
The project can be started in RStudio by executing the file Taka_A1_A2_only.Rproj. The folder structure is as follows:
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bash/ contains the code to align, quantify and generate new reference annotatios data using HISAT and Stringtie. Bash_coverageTables.TXT and Bash_Hisat_allTissues.TXT used to generate new reference and converage tables.
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bin/ contains the R scripts to run the project. The number in front of the file name indicates the order in which the code should be executed, i.e. start with 01_PCA_script.R to get PCA associated figures, then 02_PCA_3D.R, 03_Heatmap.R, and 04_PCA_Heatmap_ClustBoxplot.R. 05_Wilcoxon_test.R contains statistical test functions used for the data.
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data/ contains the data for the project. The counts files are contained in the counts folder. All the data associated with the project is saved and loaded from here.
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sc_analysis/ contains bash code to use CellRanger to create rat custom reference and the alignments of downloaded data from the Gene Expression Omnibus (GEO) with accession GSE84133. marcadores_RevFinal.csv contains main markers to identify most important cell types in pancreas.
The code is deposited on github under: https://github.com/AC-H/INGAPPP
In case of questions, please reach out to me at any time under [email protected]