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Input data requirements

Source: vignettes/data-requirement.Rmd
data-requirement.Rmd

The input data required for greatR can be either a data frame, a list of data frames, or a list of vectors, as shown below:

A single data frame input

The single data frame input or the data frame in the list must contain gene expression time-course data with all replicates. The illustrative diagram below shows the required structure of the input.

This data frame must contain reference and query expression data, and the following five columns:

  • gene_id: locus name or unique ID of each gene.
  • accession: accession or name of the reference and query data.
  • timepoint: time points of the gene expression data.
  • expression_value: desired expression values or measure of the abundance of gene or transcripts. This value can be RPM, RPKM, FPKM, TPM, TMM, or raw read counts.
  • replicate: biological replicate ID for an expression value at a particular time point.

The example below shows how the input data should look like:

gene_id accession timepoint expression_value replicate
BRAA02G018970.3C Ro18 11 0.3968734 Ro18-11-a
BRAA02G018970.3C Ro18 11 1.4147711 Ro18-11-b
BRAA02G018970.3C Col0 7 0.4667855 Col0-07-a
BRAA02G018970.3C Col0 7 0.0741901 Col0-07-b

A list of data frames as an input

If users do not have the data reference and query joined with the IDs mapped into one single data frame, there is an option of having the input data of a list of data frames. As shown in the illustrative diagram below, the list must contain both reference and query data frames with the columns as required in the single data frame input (see previous section).

The example below shows how the input list of data frames should look like:

# Load data frames from the sample data
brapa_ref_data <- system.file("extdata/brapa_SOC1_data.csv", package = "greatR") |>
  data.table::fread()

ara_query_data <- system.file("extdata/arabidopsis_SOC1_data.csv", package = "greatR") |>
  data.table::fread()

list_df <- list(
  reference = brapa_ref_data,
  query = ara_query_data
)

list_df
#> $reference
#>             gene_id accession timepoint expression_value                    replicate
#>              <char>    <char>     <int>            <num>                       <char>
#> 1: BRAA03G023790.3C      Ro18        11         1.984367  ERR_ro18_rna_seq_v3_R18A1_1
#> 2: BRAA03G023790.3C      Ro18        11         1.474974  ERR_ro18_rna_seq_v3_R18A1_2
#> 3: BRAA03G023790.3C      Ro18        11         2.194917  ERR_ro18_rna_seq_v3_R18A1_3
#> 4: BRAA03G023790.3C      Ro18        29       113.797721 ERR_ro18_rna_seq_v3_R18A10_1
#> 5: BRAA03G023790.3C      Ro18        29        94.650207 ERR_ro18_rna_seq_v3_R18A10_2
#> 6: BRAA03G023790.3C      Ro18        29       129.176178 ERR_ro18_rna_seq_v3_R18A10_3
#> 
#> $query
#>      gene_id accession timepoint expression_value                   replicate
#>       <char>    <char>     <int>            <num>                      <char>
#> 1: AT2G45660      Col0        15         76.95936 ERR_ds_klepikova_SRR1688425
#> 2: AT2G45660      Col0        14         81.96151 ERR_ds_klepikova_SRR1688328
#> 3: AT2G45660      Col0        16         59.24077 ERR_ds_klepikova_SRR1688427
#> 4: AT2G45660      Col0        15         68.85581 ERR_ds_klepikova_SRR1688426
#> 5: AT2G45660      Col0        12         64.21780 ERR_ds_klepikova_SRR2106520
#> 6: AT2G45660      Col0        10         72.98476 ERR_ds_klepikova_SRR1661475

Note here that the elements of the list must be named reference and query, the order of the element will not effect the registration process.

A list of vectors as an input

As an alternative of a list of data frame as input data, as shown above, users can also have a list of numerical vectors as their input. The illustrative diagram below shows how the input should look like:

The example below shows how the input list of vectors can be defined as an input:

# Define expression value vectors
ref_expressions <- c(1.9, 3.1, 7.8, 31.6, 33.7, 31.5, 131.4, 107.5, 116.7, 112.5, 109.7, 57.4, 50.9)
query_expressions <- c(14, 12.1, 15.9, 47, 30.9, 50.5, 80.1, 67.4, 72.9, 61.7)

list_vector <- list(
  reference = ref_expressions,
  query = query_expressions
)

list_vector
#> $reference
#>  [1]   1.9   3.1   7.8  31.6  33.7  31.5 131.4 107.5 116.7 112.5 109.7  57.4  50.9
#> 
#> $query
#>  [1] 14.0 12.1 15.9 47.0 30.9 50.5 80.1 67.4 72.9 61.7

Note that since there is no ID specified on the vectors, greatR will assign a unique ID for the reference and query pair data (see more in the register data > Using other inputs article).