 | | Data pre-processing for expression data | | | Question | | | What are the recommended expression values to import and how should I pre-process data? | | Answer | For RNA-seq data there are several normalization methods to select from.
If you use the inbuilt normalization (for Affymetrix or Agilent files) you do not have to do any pre-processing. If you are importing data using for instance the wizard you should run some normalization algorithm before loading the data.
After loading data you need to make sure you are working with logged (logarithm) values since Qlucore Omics Explorer works with logged values. If the loaded data is not logged you can log the values inside the program by checking the "log" checkbox. in the data tab.
Examples on when you (normally) need to log your data manually are for Affymetrix files when you have used PLIER or MAS5, whereas RMA and GCRMA returns logged data. Note that different implementations of the algorithms might have included a log function, so the most general recommendation is to try to estimate if your data is logged or not. A rule of thumb is that data with all values below 16 are logged.
| | Related articles | - Agilent arrays
- Feature Extraction settings
- File extensions
- How to import data (RNA-seq, Illumina, Affymetrix, 10x, Agilent, Wizard, tab separated, csv, txt, bam)
- Absent/present calls
- Affymetrix Registration button not working
- Data with many samples
- How does Qlucore calculate the length of the gene to do the normalization?
- How is the normalization (mean=0, Var=1) done in Omics Explorer?
- Import Affymetrix data
- Normalization of imported RNA-seq data
- Normalization of RNAseq data in Qlucore Omics Explorer
- Normalization using housekeeping genes
- Normalization Z-score (mean=0, var=1) calculations
- Normalizing PCR (QPCR or Q-PCR) data
- Quantile normalization and eliminated factors
- Save RNA-seq or Affymetrix files as .gedata
- Selecting Affymetrix probesets using Jetset or collapse
- Supported data types
- These CHP files do not contain probeset IDs.
- TPM values for RNASeq
- Two colored arrays
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