Chapter 1 📥 Load data into R environment

1.1 Organization of built-in data

The built-in data follows several specifications for constructing:

① They are constructed into a SummarizedExperiment object using the SummarizedExperiment() function in SummarizedExperiment package.

② The assays of the SummarizedExperiment object are stored as a SimpleList containing an expression matrix, where rows represent genes and columns represent patients.

③ The colData of the SummarizedExperiment object is a table(DFrame object of S4), where the row names must be the same as the column names of the expression matrix. The column names of the table represent the clinical information of patients. The detailed information about the column names is presented below.

column name Recommend value Description Necessity in tigeR analysis
sample id character The sample identification. ✓
patient_name character The patient identification. ✕
dataset_id character The dataset identification. ✕
dataset_group character ✕
Treatment PRE/POST The patient sample is collected after Treatment or before Treatment ✓
response CR/MR/PR/PD/SD/NR/R/N The Immunotherapy response. ✕
response_NR R/N The Immunotherapy response which only contains R or N. ✓
M.stage character The M stage of patients. ✕
overall.survival..days. value The number of days, months or years of survival time of patients.(all samples must be the same unit) ✓
vital.status Alive/Dead The survival status of patient. ✓
Total.Mutation numeric The total mutation gene numbers. ✕
Gender M/F The gender of patient. ✕
Therapy character The anti-tumor therapy on patients. ✕
age_start numeric When the tumor is diagnosed. ✕
tumor_type character The type of tumor. ✕
seq_type character The sequencing type. ✕
id character The identification of dataset. ✕

1.2 Obtain data from tigeR web server

Dataloader(c(1,2,3), use_source="Web Server")

1.3 Obtain data from ExperimentHub

Dataloader(c(1,2,3), use_source="ExperimentHub)

1.4 Pre-processing of Custom Data

 When importing custom data, you need to prepare at least one expression matrix (rows for genes, columns for samples), along with the corresponding column information table, which should include at least the following information:

  • sample id
  • Treatment (PRE/POST)
  • response_NR (R/N)
  • overall.survival..days. (Missing data is also acceptable)
  • vital.status (Missing data is also acceptable)

 Here is a brief example:

## Construt FPKM Matrix
genes <- c("5S_rRNA", "A1BG", "A1BG-AS1")
samples <- c("SRR3184279", "SRR3184280", "SRR3184281")

mtr <- matrix(
  c(0.04115157, 0.01311394, 0.02275499,
    0.07774626, 0.29494916, 0.11743900,
    2.01782650, 0.83763027, 0.77378394),
  nrow = 3, ncol = 3, byrow = TRUE, 
  dimnames = list(genes, samples))

## Construct Clinical Information Table
data <- data.frame(
  sample_id = c("SRR3184279", "SRR3184280", "SRR3184281"),
  Treatment = c("PRE", "PRE", "PRE"),
  response_NR = c("N", "R", "R"),
  overall_survival_days = c(607, 927, 948),
  vital_status = c("Dead", "Alive", "Alive"),
  stringsAsFactors = FALSE)

## Construct SummarizedExperiment Object
SE <- SummarizedExperiment::SummarizedExperiment(
  assays = list(fpkm = mtr),
  colData = data)

SE
# class: SummarizedExperiment
# dim: 3 3
# metadata(0):
#   assays(1): fpkm
# rownames(3): 5S_rRNA A1BG A1BG-AS1
# rowData names(0):
#   colnames(3): SRR3184279 SRR3184280 SRR3184281
# colData names(5): sample_id Treatment response_NR overall_survival_days
# vital_status