Python implementation of common RNA-seq normalization methods:
- CPM (Counts per million)
- FPKM (Fragments per kilobase million)
- TPM (Transcripts per million)
- UQ (Upper quartile)
- CUF (Counts adjusted with UQ factors)
- TMM (Trimmed mean of M-values)
- CTF (Counts adjusted with TMM factors)
For in-depth description of methods see documentation.
- Pure Python implementation (no need for R, etc.)
- Compatible with Scikit-learn
- Command line interface
- Verbose documentation
- Validated method implementation
We recommend installing RNAnorm with pip:
pip install rnanorm
The implemented methods can be executed from Python or from the command line.
The most common use case is to run normalization from Python:
>>> from rnanorm.datasets import load_toy_data
>>> from rnanorm import FPKM
>>> dataset = load_toy_data()
>>> # Expressions need to have genes in columns and samples in rows
>>> dataset.exp
Gene_1 Gene_2 Gene_3 Gene_4 Gene_5
Sample_1 200 300 500 2000 7000
Sample_2 400 600 1000 4000 14000
Sample_3 200 300 500 2000 17000
Sample_4 200 300 500 2000 2000
>>> fpkm = FPKM(dataset.gtf_path).set_output(transform="pandas")
>>> fpkm.fit_transform(dataset.exp)
Gene_1 Gene_2 Gene_3 Gene_4 Gene_5
Sample_1 100000.0 100000.0 100000.0 200000.0 700000.0
Sample_2 100000.0 100000.0 100000.0 200000.0 700000.0
Sample_3 50000.0 50000.0 50000.0 100000.0 850000.0
Sample_4 200000.0 200000.0 200000.0 400000.0 400000.0
Normalization from the command line is also supported. To list available methods and general help:
rnanorm --help
Get info about a particular method, e.g., CPM:
rnanorm cpm --help
To normalize with CPM:
rnanorm cpm exp.csv --out exp_cpm.csv
File exp.csv needs to be comma separated file with genes in columns and
samples in rows. Values should be raw counts. The output is saved to
exp_cpm.csv. Example of input file:
cat exp.csv ,Gene_1,Gene_2,Gene_3,Gene_4,Gene_5 Sample_1,200,300,500,2000,7000 Sample_2,400,600,1000,4000,14000 Sample_3,200,300,500,2000,17000 Sample_4,200,300,500,2000,2000
One can also provide input through standard input:
cat exp.csv | rnanorm cpm --out exp_cpm.csv
If file specified with --out already exists the command will fail. If you
are sure that you wish to overwrite, use --force flag:
cat exp.csv | rnanorm cpm --force --out exp_cpm.csv
If no file is specified with --out parameter, output is printed to standard
output:
cat exp.csv | rnanorm cpm > exp_cpm.csv
Methods TPM and FPKM require gene lengths. These can be provided either with GTF
file or with "gene lengths" file. The later is a two columns file. The first
column should include the genes in the header of exp.csv and the second
column should contain gene lengths computed by union exon model:
# Use GTF file rnanorm tpm exp.csv --gtf annotations.gtf > exp_out.csv # Use gene lengths file rnanorm tpm exp.csv --gene-lengths lenghts.csv > exp_out.csv # Example of gene lengths file cat lenghts.csv gene_id,gene_length Gene_1,200 Gene_2,300 Gene_3,500 Gene_4,1000 Gene_5,1000
To learn about contributing to the code base, read the Contributing section.
If you are using RNAnorm in your research, please cite as suggested by "Cite this repository" section in the side panel of this page.