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

To learn about contributing to the code base, read the Contributing section.