ribonorma 1.2

Implements additional normalisation methods for RNA Sequencing.

Ribonorma

As part of the paper

Installation

Installation can be done with Pip. Python 3.6+.

pip install ribonorma

pip3 install ribonorma

How to use

Command line usage

1. Suppose you have two files, one file with the raw RNASeq count data (example) and one file with the phenotype file data (example).

2. Run ribonorma-normalise

Python code usage

import csv
from ribonorma import ribonorma

reads = list(csv.read( ... )) # Reads
gene_length = [] # List of gene lengths

conditions = ["Standard media", "Standard media", "Standard media", "Super media", "Super media", "Super media"] # Example conditions

normalised_counts = ribonorma.tpmr(reads, gene_length, conditions, percent_housekeep=10)

ribonorma.tpm(reads, gene_length)

• reads: 1D list of read counts
• gene_length: 1D list of individual gene lengths

ribonorma.tpmm(samples, gene_length)

• samples: 2D list of sample read counts - [sample x count]
• gene_length: 1D list of individual gene lengths

ribonorma.tpmr(samples, gene_length, experimental_conditions, percent_housekeep=10)

• samples: 2D list of sample read counts - [sample x count]
• gene_length: 1D list of individual gene lengths
• experimental_conditions: 1D list of individual experimental conditions, same size as samples
• alpha: floating point value of percent housekeep as stated in the paper

ribonorma.tpmr_2(samples, gene_length, experimental_conditions, percent_housekeep=10)

• samples: 2D list of sample read counts - [sample x count]
• gene_length: 1D list of individual gene lengths
• experimental_conditions: 1D list of individual experimental conditions, same size as samples
• alpha: floating point value of percent housekeep as stated in the paper