Preparing SomaLogic ADAT Data for Upload to Mass Dynamics

This FAQ provides guidance and an example R script for transforming SomaLogic ADAT data into a wide-format table with intensities. The output is a *.csv file that can be uploaded to the Mass Dynamics platform.

Sample data: https://somalogic.com/datadelve-statistics/

Expected SomaLogic Input Format

• A .adat file exported from SomaLogic assays.
• Each sample contains protein measurements (intensities) for a set of analytes uniquely identified by AptName.
  
  

Required fields or derived columns:

• SampleId
  
  
• PlatePosition (to uniquely identify calibrators/QC samples)
  
  
• Intensity values (in columns prefixed with seq.)
  
  
• Analyte metadata: AptName, UniProt, EntrezGeneSymbol, TargetFullName
  
  

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Prepare the Data for Mass Dynamics

• Read the ADAT file into R using read_adat() from the SomaDataIO R package.
• The ADAT file is in a wide format but with samples as rows and analytes as columns. To make it suitable for Mass Dynamics the file needs to be converted to a wide format where analytes represent rows and samples are the columns.
• Analyte metadata are retrieved and merged with the measurement data using getAnalyteInfo() and a join on AptName.

R Code snippet to prepare the data

Upload to Mass Dynamics

1. Upload the intensities_somalogic.csv file

2. Follow the steps to select the columns containing protein intensities

3. Map protein metadata as follows:

• AptName-> ProteinGroup
• Uniprot -> ProteinIds
• EntrezGeneSymbol -> GeneName
• TargetFullName -> Description

 

4. Follow the steps to upload the experiment design 

Code in text format

library(SomaDataIO)

library(dplyr)

library(tidyr)

 

# Read SomaLogic ADAT file

my_adat <- read_adat("path/to/your_data.adat")

 

# Retrieve analyte metadata

analyte_infos <- getAnalyteInfo(my_adat)

 

# Convert wide-format intensity data to long format to retrieve intensities

my_adat_long <- my_adat %>% 

  pivot_longer(cols = starts_with("seq."), names_to = "AptName", values_to = "Intensity")

 

# Join long data with analyte metadata

my_adat_long <- left_join(my_adat_long, analyte_infos, by = "AptName")

 

# Create unique sample name using SampleId and PlatePosition

my_adat_long <- my_adat_long %>% 

  unite(SampleName, SampleId, PlatePosition, sep = "-", remove = FALSE)

 

# Pivot to wide format: one row per protein, one column per sample

intensities_table <- my_adat_long %>%

  pivot_wider(

    id_cols = c(AptName, UniProt, EntrezGeneSymbol, TargetFullName),

    names_from = SampleName,

    values_from = Intensity

  )

 

# Write to CSV

write_csv(intensities_table, "path/to/intensities_somalogic.csv")