This repository includes code for processing data of hasm_silac_protein. hasm_silac_protein_total.Rmd script has code for the results.
This pipeline is designed to be used in R environment.
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Install the R statistical package. We used version 4.0.4.
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Install the following R packages, which can be obtained using either the install.packages function in R or via the Bioconductor framework:
- limma
- proDA
- sva
- calibrate
- ggplot
- fgsea
- tidyverse
- data.table
Using 9samples_raw.txt to generate the differentially expressed proteins. The input file is 9samples_raw.txt, by using dep_AC2_AC6_lacZ.R, the output file are AC2_VS_lacZ_DEP01.txt and AC6_VS_lacZ_DEP01.txt. Then, the volcano plots of the whole proteins were made. The green color indicated the differentially expressed proteins.
Input the differentially expresed protein into david functional annotation bioinformatics, generate the GO analysis. Only picked the Description, Gene_Count, P_Value and Enrichment_Ratio value to generate the txt fle. The input files are AC2_01_CC.txt, AC6_01_CC.txt and AC6_01_MF.txt files,by using david_AC2_AC6_lacZ.R, the plots of the cellular component and molecular function can be drawn.
Using c2.cp.v7.2.symbols.gtm and c2.cp.kegg.v7.2.symbols.gmt, gene name and the t-test value to generate the kegg and canonical pathway. The input files are AC2_vs_lacZ_fgsea01.txt and AC6_vs_lacZ_fgsea01.txt, by using fgsea_AC2_AC6_lacZ.R, can get the kegg and the whole canonical pathways.
- Moom R. Roosam. roosan@chapman.edu
- Yue Li. yli1@chapman.edu