OMIQ Data Extraction Tutorial

How to extract data from OMIQ

Adrien Mazuel
adrien.mazuel@inserm.fr
Eugénie Lohmann
eugenie.lohmann@inserm.fr

June 9, 2023

Extracting Features with OMIQ

In this tutorial, we’ll guide you through the process of extracting features using OMIQ

The different sections we will cover

  • Abundance table
  • MFI table
  • Metadata table

Workflow

Perform your classic OMIQ workflow.

Scaling -> Gating -> Subsampling -> Dimensionality reduction -> Clustering

Learn more: OMIQ Workflow

Export Abundance

Samples of interest selection

Select all the fcs for which you want statistics

Metacluster counts extraction

Second step is to ignore the « Features » panel and go straight to “Counts” panel

Cluster Selection

Metric Selection: « Count » in our case

Exporting an abundance table

Bypass the « Count Ratio » and « Metadata » panel and go to “Configuration” panel

Keep these settings and you’re now ready to export the data table

Example of an abundance table

The final table will be as follows

file MC01|count MC02|count MC03|count MC04|count MC05|count MC06|count MC07|count MC08|count MC09|count MC10|count
raw_D1.fcs 226 139 729 360 613 1083 319 610 368 553
raw_D2.fcs 245 175 741 350 594 1025 330 628 378 534
raw_D3.fcs 227 164 709 369 605 972 354 708 377 515
raw_P1.fcs 594 497 325 583 364 617 533 360 905 222
raw_P2.fcs 684 494 285 551 345 629 542 360 893 217
raw_P3.fcs 632 461 320 574 339 619 543 385 900 227

Export MFI

The first step is similar to abundance extraction

Selection of samples of interest

Select all the fcs for which you wish to obtain statistics.

Median marker value for each Metaclusters

Cluster Selection

Metric Selection, « Median » in our case

Marker Selection

Export of MFI database

Bypass the « Counts », « Count Ratio » and « Metadata » panel and go to “Configuration” panel

  • Set Layout Selection to Database
  • Choose either raw or scaled MFI (asinh)

Example MFI table

The final table will be as follows

file value measure filter ftr (prim) ftr (sec)
raw_D1.fcs 2.7100 median MC01 146 CD64-146
raw_D1.fcs 2.5300 median MC02 146 CD64-146
raw_D1.fcs 0.0341 median MC03 146 CD64-146
raw_D1.fcs 2.5700 median MC04 146 CD64-146
raw_D1.fcs 0.0813 median MC05 146 CD64-146
raw_D1.fcs 0.7820 median MC06 146 CD64-146

Export Metadata

The first step is similar to abundance extraction

Samples of interest selection

Select all the fcs for which you want statistics

Extract the number of cells per patients

Second step is to ignore the “Features” panel and go straight to “Counts” panel

Select Unfiltered

Metric Selection, « Count » in our case

This step allows us to add the total number of cells per sample

Select samples informations

Ignore the « Count Ratio » panel and go straight to “Metadata” panel

Select all the metadata of interest to your analysis

Export of Metadata table

Keep these settings and you’re now ready to export the data table

Example Metadata table

The final table will be as follows

file Unfiltered|count Group Individuals
raw_D1.fcs 5000 Donors ind-1
raw_D2.fcs 5000 Donors ind-2
raw_D3.fcs 5000 Donors ind-3
raw_P1.fcs 5000 Patients ind-1
raw_P2.fcs 5000 Patients ind-2
raw_P3.fcs 5000 Patients ind-3

Omiq feature extraction for R.AnalytiCyte