GO analysis
ERM
2023-01-31
Last updated: 2023-01-31
Checks: 7 0
Knit directory: Cardiotoxicity/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | 848eb1a | reneeisnowhere | 2023-01-31 | updating GO plots |
| Rmd | 82b31a0 | reneeisnowhere | 2023-01-31 | updating GEA |
| Rmd | 34a525c | reneeisnowhere | 2023-01-26 | link update |
| html | 41b5f9c | reneeisnowhere | 2023-01-23 | Build site. |
| Rmd | dc890ec | reneeisnowhere | 2023-01-23 | Updating the source dir |
| Rmd | a78eab0 | reneeisnowhere | 2023-01-23 | updated Go analysis |
| Rmd | d9edc06 | reneeisnowhere | 2023-01-20 | try a little update later |
| Rmd | b7eac76 | reneeisnowhere | 2023-01-20 | updating GO |
| html | 6c21cf8 | reneeisnowhere | 2023-01-20 | Build site. |
| Rmd | 443a9f3 | reneeisnowhere | 2023-01-20 | adding in GO analysis |
GO Analysis
I have created several files from the RNA analysis that contain the significant genes(determined by adj.P.val < 0.1) from each Time and Condition. The names of the files are in the following format: ‘sigV’+Drug(2 letters)+time.
example: ‘sigVDA3.txt’ means this file contains the significant DE genes from the Daunorubicin 3 hour compared to Vehicle Control 3 hour analysis
library(gprofiler2)
library(tidyverse)
library(readr)
library(BiocGenerics)
library(gridExtra)
library(VennDiagram)The analysis is based on all genes that passed the rowMeans>0 from the previous page link
Below is the analysis of differentially expressed genes for each treatment at 3 hours and 24 hours.
I first looked at the data with all genes from the sigDA3 dataset. I used the list of all genes based on my rowMeans>0 filtering as background.
Analysis of Up versus Down
I then separated the VDA3 file by log2 Fold Change to see how the gene sets are enriched. Nothing showed up in the GO-BP/CC/MG-down regulated gene-set at a significant level, p<0.05.
I next wanted to see what happened at 24 hours with daunorubicin. I used the sigVDA24 file to do this.
unfortunately the enrichment below 0.0001
Graphing specific gene expression
First get a list of genes you want to see. There are multiple was to “see” these. I used the word ‘apple’ to store my list
sessionInfo()R version 4.2.2 (2022-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19044)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.utf8
[2] LC_CTYPE=English_United States.utf8
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.utf8
attached base packages:
[1] grid stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] VennDiagram_1.7.3 futile.logger_1.4.3 gridExtra_2.3
[4] BiocGenerics_0.42.0 forcats_1.0.0 stringr_1.5.0
[7] dplyr_1.1.0 purrr_1.0.1 readr_2.1.3
[10] tidyr_1.3.0 tibble_3.1.8 ggplot2_3.4.0
[13] tidyverse_1.3.2 gprofiler2_0.2.1 workflowr_1.7.0
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