1. Knowledge Hub
  2. Methods
  3. NanoString nCounter Gene Expression

How to replicate the ROSALIND Analysis settings in nSolver Advanced Analysis

The Rosalind data analysis pipeline for the input of RCC files (ie raw data) was validated to reproduce the nSolver/Advanced Analysis with the following settings:

Analysis Set-up

  1. Data input: RCC files 
  2. The covariate setting in nSovler AA is the confounder setting in Rosalind
  3. Analysis Type: Custom Analysis (vs Quick Analysis)
  4. Check “Omit Low Count Data” with default settings of Auto: checked, Threshold Count Value: 20, Observation Frequency: 0.5
  5. Default threshold settings: 20 counts, and an observation frequency of 0.5 (eg 50%) 

Normalization default with the GeNorm algorithm

Differential Expression

  1. Differential Expression with the Fast analysis setting
  2. P-value Adjustment: Benjamini-Hockberg

Cell type Profiling 

  1. Column Specifying the Cell Types' Characteristic Probes: Use Default (Cell Type)
  2. Creating Signatures: Dynamically select a subset
  3. P-value Threshold for Reporting Cell Type Abundance: Custom, p-value= 0.05 
  4. Show results for: Raw Cell Type Abundance (checked) Relative Cell Type Abundance, Cell Type Contrasts: Use Defaults selected

Common differences in the analysis are: 

  1. Uploading normalized data
  2. Running the normalization on a different set of RCC data in the nSolver AA and Rosalind Analyses will provide different results when the comparison is done on the same samples.  
  3. P-value adjustment not selected for Benjamini Hochberg