Area of Neuroscience, Scuola Internazionale Superiore di Studi Avanzati (SISSA), Trieste 34136, Italy.
Central RNA Laboratory, Istituto Italiano di Tecnologia, Genova 16163, Italy.
Bioinformatics. 2022 Sep 15;38(18):4430-4433. doi: 10.1093/bioinformatics/btac526.
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.
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 data are available at Bioinformatics online.
转座元件 (TEs) 在关键的生物途径中发挥着关键作用。因此，最近开发了几种能够定量其表达的工具。然而，许多现有的工具缺乏区分自主表达的 TEs 和嵌入在规范编码/非编码非 TEs 转录本中的 TE 片段转录的能力。因此，给定 TE 的表达的明显变化可能仅仅反映了包含 TE 衍生序列的转录本表达的变化。为了解决这个问题，我们开发了 TEspeX，这是一种在共识水平上定量 TE 表达的流水线。TEspeX 使用 Illumina RNA-seq 短读长来定量 TE 的表达，避免了对嵌入规范转录本中的非活性 TE 片段衍生的读长进行计数。
该工具是用 python3 实现的，根据 GNU 通用公共许可证 (GPL) 分发，并可在 Github 上获得，网址为 https://github.com/fansalon/TEspeX（Zenodo 网址：https://doi.org/10.5281/zenodo.6800331）。
补充数据可在生物信息学在线获得。
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