hd_initialize() initializes an HDAnalyzeR object with the data, metadata, and other parameters. This object can be used to run various analyses in the package.
Usage
hd_initialize(
dat,
metadata = NULL,
is_wide = FALSE,
sample_id = "DAid",
var_name = "Assay",
value_name = "NPX"
)Arguments
- dat
A tibble containing the omics data.
- metadata
A tibble containing the metadata. Default is NULL.
- is_wide
A logical indicating if the data is in wide format. Default is FALSE.
- sample_id
The name of the column containing the sample IDs. Default is "DAid".
- var_name
The name of the column containing the variable names. Default is "Assay".
- value_name
The name of the column containing the values. Default is "NPX".
Details
It is strongly recommended to use this function to initialize an HDAnalyzeR
object before starting any analysis. This initialization step ensures that
your input data and metadata are correctly formatted and compatible with the
package. Specifically, the function validates your data and automatically
converts it to wide format if provided in long format (is_wide).
While it is possible to use HDAnalyzeR functions on data outside of an HDAnalyzeR object, users must ensure that the data adheres to the required structure: the first column must contain sample IDs, followed by numeric columns (protein expression) in wide format. Additionally, the metadata must include the same set of sample IDs. Proper initialization or careful adherence to these requirements is crucial for accurate and efficient analysis. Defaults are provided according to the Human Disease Blood Atlas Olink data format.
Examples
# Initialize an HDAnalyzeR object
hd_initialize(example_data, example_metadata)
#> $data
#> # A tibble: 586 × 101
#> DAid AARSD1 ABL1 ACAA1 ACAN ACE2 ACOX1 ACP5 ACP6 ACTA2
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 DA00001 3.39 2.76 1.71 0.0333 1.76 -0.919 1.54 2.15 2.81
#> 2 DA00002 1.42 1.25 -0.816 -0.459 0.826 -0.902 0.647 1.30 0.798
#> 3 DA00003 NA NA NA 0.989 NA 0.330 1.37 NA NA
#> 4 DA00004 3.41 3.38 1.69 NA 1.52 NA 0.841 0.582 1.70
#> 5 DA00005 5.01 5.05 0.128 0.401 -0.933 -0.584 0.0265 1.16 2.73
#> 6 DA00006 6.83 1.18 -1.74 -0.156 1.53 -0.721 0.620 0.527 0.772
#> 7 DA00007 NA NA 3.96 0.682 3.14 2.62 1.47 2.25 2.01
#> 8 DA00008 2.78 0.812 -0.552 0.982 -0.101 -0.304 0.376 -0.826 1.52
#> 9 DA00009 4.39 3.34 -0.452 -0.868 0.395 1.71 1.49 -0.0285 0.200
#> 10 DA00010 1.83 1.21 -0.912 -1.04 -0.0918 -0.304 1.69 0.0920 2.04
#> # ℹ 576 more rows
#> # ℹ 91 more variables: ACTN4 <dbl>, ACY1 <dbl>, ADA <dbl>, ADA2 <dbl>,
#> # ADAM15 <dbl>, ADAM23 <dbl>, ADAM8 <dbl>, ADAMTS13 <dbl>, ADAMTS15 <dbl>,
#> # ADAMTS16 <dbl>, ADAMTS8 <dbl>, ADCYAP1R1 <dbl>, ADGRE2 <dbl>, ADGRE5 <dbl>,
#> # ADGRG1 <dbl>, ADGRG2 <dbl>, ADH4 <dbl>, ADM <dbl>, AGER <dbl>, AGR2 <dbl>,
#> # AGR3 <dbl>, AGRN <dbl>, AGRP <dbl>, AGXT <dbl>, AHCY <dbl>, AHSP <dbl>,
#> # AIF1 <dbl>, AIFM1 <dbl>, AK1 <dbl>, AKR1B1 <dbl>, AKR1C4 <dbl>, …
#>
#> $metadata
#> # A tibble: 586 × 9
#> DAid Sample Disease Stage Grade Sex Age BMI Cohort
#> <chr> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr>
#> 1 DA00001 AML_syn_1 AML 2 NA F 42 22.7 UCAN
#> 2 DA00002 AML_syn_2 AML Unknown NA M 69 33.1 UCAN
#> 3 DA00003 AML_syn_3 AML 2 NA F 61 26.2 UCAN
#> 4 DA00004 AML_syn_4 AML Unknown NA M 54 28.1 UCAN
#> 5 DA00005 AML_syn_5 AML 2 NA F 57 21.4 UCAN
#> 6 DA00006 AML_syn_6 AML Unknown NA M 86 33.9 UCAN
#> 7 DA00007 AML_syn_7 AML 1 NA F 85 28.7 UCAN
#> 8 DA00008 AML_syn_8 AML 3 NA F 88 32.6 UCAN
#> 9 DA00009 AML_syn_9 AML Unknown NA M 80 26.1 UCAN
#> 10 DA00010 AML_syn_10 AML 3 NA M 48 33.8 UCAN
#> # ℹ 576 more rows
#>
#> $sample_id
#> [1] "DAid"
#>
#> $var_name
#> [1] "Assay"
#>
#> $value_name
#> [1] "NPX"
#>
#> attr(,"class")
#> [1] "HDAnalyzeR"