HASM_SILAC

This repository includes code for processing data of hasm_silac_protein. hasm_silac_protein_total.Rmd script has code for the results.

Install the software, download the data and set up the directory

This pipeline is designed to be used in R environment.

1. Install the R statistical package. We used version 4.0.4.

2. 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

dep_AC2_AC6_VS_lacZ

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.

david_AC2_AC6_VS_lacZ

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.

fgsea_AC2_AC6_VS_lacZ

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.

Contact information

• Moom R. Roosam. [email protected]
• Yue Li. [email protected]