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好久没有发布公众号文章和B站视频了,

用户可以直接使用如下链接访问PCAS Shinyapp:https://jingle.shinyapps.io/PCAS/

也可以安装该R包:

   remotes::install_github("WangJin93/PCAS") 

输入PCAS_app()函数运行PCAS app, 该APP的使用参照本工具的文章:

Citation: Wang J, Song X, Wei M, Qin L, Zhu Q, Wang S, Liang T, Hu W, Zhu X, Li J. PCAS: An Integrated Tool for Multi-Dimensional Cancer Research Utilizing Clinical Proteomic Tumor Analysis Consortium Data. International Journal of Molecular Sciences. 2024; 25(12):6690. https://doi.org/10.3390/ijms25126690IF: 5.6 B2

或B站视频:

https://www.bilibili.com/video/BV1W6421Z7nr/

PCAS包主要函数:

  1. get_data():

Description

Get the CPTAC data by using the api. All results saved in MySQL database.

Usage

get_data(
  table = "LUAD_Academia_protein",
  action = "expression",
  genes = c("GAPDH", "TNS1")
)

Arguments

table

For action = expression, use dataset$Abbre to get all tables; For action = clinic, remove _protein/_mRNA/_Phospho from dataset$Abbre.

action

“expression”, “degs” or “clinic”.

gene

Gene symbols, you can input one or multiple symbols.

2. get_expr_data()

Description

Get the mRNA/protein expression data in CPTAC database.

Usage

get_expr_data(
  datasets = c("LUAD_CPTAC_protein", "LSCC_CPTAC_protein"),
  genes = c("TP53", "TNS1")
)

Arguments

datasets

Dataset names, you can input one or multiple datasets. Use ‘dataset$Abbre’ to get all datasets.

genes

Gene symbols, you can input one or multiple symbols.

3. Get_DEGs_result()

Description

Get the results of different expression analysis between tumor and normal samples in CPTAC datasets.

Usage

   get_DEGs_result(dataset = "LUAD_CPTAC_protein", method = "t.test") 

Arguments

dataset

Use dataset$Abbre to get all tables.

method

“limma” or “t.test”.

4. merge_clinic_data()

Description

Get clinic data and merge it with expression data.

Usage

merge_clinic_data(cohort = “LUAD_APOLLO”, data_input)

Arguments

cohort

Data cohort, for example, “LUAD_APOLLO”, “LUAD_CPTAC”.

data_input

Expression data obtained from get_expr_data() function.

5. cor_cancer_genelist()

Description

Perform correlation analysis of the mRNA/protein expression data in CPTAC database.

Usage

cor_cancer_genelist(
  dataset1 = "LUAD_CPTAC_protein",
  id1 = "STAT3",
  dataset2 = "LUAD_CPTAC_mRNA",
  id2 = c("TNS1", "TP53"),
  sample_type = c("Tumor", "Normal"),
  cor_method = "pearson"
)

Arguments

dataset1

Dataset name. Use ‘dataset$Abbre’ to get all datasets.

id1

Gene symbol, you can input one gene symbols.

dataset2

Dataset name. Use ‘dataset$Abbre’ to get all datasets.

id2

Gene symbols, you can input one or multiple symbols.

sample_type

Sample type used for correlation analysis, default all types: c(“Tumor”, “Normal”).

cor_method

cor_method for correlation analysis, default “pearson”.

6. cor_pancancer_genelist()

Description

Perform correlation analysis of the mRNA/protein expression data in CPTAC database.

Usage

cor_pancancer_genelist(
  df,
  geneset_data,
  sample_type = c("Tumor", "Normal"),
  cor_method = "pearson"
)

Arguments

df

The expression data of the target gene in multiple datasets, obtained by the get_expr_data() function.

geneset_data

The expression data of a genelist in multiple datasets, obtained by the get_expr_data() function.

sample_type

Sample type used for correlation analysis, default all types: c(“Tumor”, “Normal”).

cor_method

Method for correlation analysis, default “pearson”.

7. cor_pancancer_drug()

Description

Calculate the correlation between target gene expression and anti-tumor drug sensitivity in multiple datasets.

Usage

cor_pancancer_drug(
  df,
  cor_method = "pearson",
  Target.pathway = c("Cell cycle")
)

Arguments

df

The expression data of the target gene in multiple datasets, obtained by the get_expr_data() function.

cor_method

Method for correlation analysis, default “pearson”.

Target.pathway

The signaling pathways of anti-tumor drug targets, default “Cell cycle”. Use “drug_info”to get the detail infomation of these drugs.

8. cor_pancancer_TIL

Description

Calculate the correlation between target gene expression and immune cells infiltration in multiple datasets.

Usage

   cor_pancancer_TIL(df, cor_method = "spearman", TIL_type = c("TIMER")) 

Arguments

df

The expression data of the target gene in multiple datasets, obtained by the get_expr_data() function.

cor_method

Method for correlation analysis, default “pearson”.

TIL_type

Algorithm for calculating immune cell infiltration, default “TIMER”.

9. viz_TvsN()

Description

Visualizing the different expression of mRNA/protein expression data between Tumor and Normal tissues in CPTAC database.

Usage

viz_TvsN(
  df,
  df_type = c("single", "multi_gene", "multi_set"),
  Show.P.value = TRUE,
  Show.P.label = TRUE,
  Method = "t.test",
  values = c("#00AFBB", "#FC4E07"),
  Show.n = TRUE,
  Show.n.location = "default"
)

10.viz_DEGs_volcano()

Description

Plotting volcano plot for DEGs between tumor and normal samples in CPTAC datasets.

Usage

viz_DEGs_volcano(
  df,
  p.cut = 0.05,
  logFC.cut = 1,
  show.top = FALSE,
  show.labels = NULL
)

Arguments

cohort

Data cohort, for example, “LUAD_APOLLO”, “LUAD_CPTAC”.

data_input

Expression data obtained from get_expr_data() function.

11. viz_cor_heatmap()

Description

Presenting correlation analysis results using heat maps based on ggplot2.

Usage

   viz_cor_heatmap(r, p) 

Arguments

r

The correlation coefficient matrix r of the correlation analysis results obtained from the functions cor_pancancer_genelist(), cor_pancancer_TIL(), and cor_pancancer_drug().

p

The P-value matrix p of the correlation analysis results obtained from the functions cor_pancancer_genelist(), cor_pancancer_TIL(), and cor_pancancer_drug().

12. viz_corplot()

Description

Scatter plot with sample size (n), correlation coefficient (r) and p value (p.value).

Usage

viz_corplot(
  data,
  a,
  b,
  method = "pearson",
  x_lab = " relative expression",
  y_lab = " relative expression"
)

Arguments

data

A gene expression dataset with at least two genes included, rows represent samples, and columns represent gene expression in the matrix.

a

Gene A

b

Gene B

method

Method for correlation analysis, “pearson” or “spearman”.

x_lab

X-axis label.

y_lab

Y-axis label.

13. viz_phoso_sites()

Description

Query phosphorylation site information of target proteins based on CPTAC database phosphorylation proteomics data or UniProt database.

Usage

   viz_phoso_sites(gene = "YTHDC2", phoso_infoDB = "CPTAC") 

Arguments

gene

Gene/protein symbol.

phoso_infoDB

Database for extracting phosphorylation site information. only supports ‘UniProt’ and ‘CPTAC’, Default “CPTAC”.

14. Citation:

Wang J, Song X, Wei M, Qin L, Zhu Q, Wang S, Liang T, Hu W, Zhu X, Li J. PCAS: An Integrated Tool for Multi-Dimensional Cancer Research Utilizing Clinical Proteomic Tumor Analysis Consortium Data. International Journal of Molecular Sciences. 2024; 25(12):6690. https://doi.org/10.3390/ijms25126690

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