TEspeX: consensus-specific quantification of transposable element expression preventing biases from exonized fragments

Author:

Ansaloni Federico12ORCID,Gualandi Nicolò1,Esposito Mauro1,Gustincich Stefano2,Sanges Remo12

Affiliation:

1. Area of Neuroscience, Scuola Internazionale Superiore di Studi Avanzati (SISSA) , Trieste 34136, Italy

2. Central RNA Laboratory, Istituto Italiano di Tecnologia , Genova 16163, Italy

Abstract

Abstract Summary Transposable elements (TEs) play key roles in crucial biological pathways. Therefore, several tools enabling the quantification of their expression were recently developed. However, many of the existing tools lack the capability to distinguish between the transcription of autonomously expressed TEs and TE fragments embedded in canonical coding/non-coding non-TE transcripts. Consequently, an apparent change in the expression of a given TE may simply reflect the variation in the expression of the transcripts containing TE-derived sequences. To overcome this issue, we have developed TEspeX, a pipeline for the quantification of TE expression at the consensus level. TEspeX uses Illumina RNA-seq short reads to quantify TE expression avoiding counting reads deriving from inactive TE fragments embedded in canonical transcripts. Availability and implementation The tool is implemented in python3, distributed under the GNU General Public License (GPL) and available on Github at https://github.com/fansalon/TEspeX (Zenodo URL: https://doi.org/10.5281/zenodo.6800331). Supplementary information Supplementary data are available at Bioinformatics online.

Funder

International School for Advanced Studies

Istituto Italiano di Tecnologia

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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