Cellular liberality is measurable as Lempel-Ziv complexity of fastq files

TL;DR

This paper introduces a novel method to measure cellular liberality directly from raw transcriptome data using Lempel-Ziv complexity, eliminating the need for extensive bioinformatic processing and reference genome dependence.

Contribution

It proposes a new approach to quantify cellular dedifferentiation and differentiation by measuring data compression rate directly from raw fastq files, simplifying analysis.

Findings

Lempel-Ziv complexity correlates with cellular differentiation status.

Method reduces computational resources and processing time.

Independent of reference genome data.

Abstract

Many studies used the Shannon entropy of transcriptome data to determine cell dedifferentiation and differentiation. The collection of evidence has strengthened the certainty that the transcriptome's Shannon entropy may be used to quantify cellular dedifferentiation and differentiation. Quantifying this cellular status is being justified, we propose the term liberality for the quantitative value of cellular dedifferentiation and differentiation. In previous studies, we must convert the raw transcriptome data into quantitative transcriptome data through mapping, tag counting, assembling, and more bioinformatic processing to calculate the liberality. If we could remove this conversion step from estimating liberality, we could save computing resources and time and remove technical difficulties in using the computer. In this study, we propose a method of calculating cellular liberality without those transcriptome data conversion processes. We could calculate liberality by measuring the compression rate of raw transcriptome data. This technique, independent of reference genome data, increased the generality of cellular liberality.