研究动态
Articles below are published ahead of final publication in an issue. Please cite articles in the following format: authors, (year), title, journal, DOI.

Transipedia.org:基于 k-mer 的大型 RNA 测序数据集探索及其在癌症数据中的应用。

Transipedia.org: k-mer-based exploration of large RNA sequencing datasets and application to cancer data.

发表日期:2024 Oct 10
作者: Chloé Bessière, Haoliang Xue, Benoit Guibert, Anthony Boureux, Florence Rufflé, Julien Viot, Rayan Chikhi, Mikaël Salson, Camille Marchet, Thérèse Commes, Daniel Gautheret
来源: GENOME BIOLOGY

摘要:

事实证明,依赖于 k-mers 的索引技术可以有效地在数千个 RNA-seq 文库中搜索 RNA 序列,但无法直接进行 RNA 定量。我们在此表明​​,任意 RNA 序列可以通过分解为 k-mers 在几秒钟内进行定量,其精度类似于传统 RNA 定量方法。使用由 1019 个 RNA-seq 样本组成的癌细胞系百科全书 (CCLE) 集合的索引,我们表明 k-mer 索引提供了一种强大的手段来揭示非参考序列以及由特定基因改变引起的变异 RNA,例如剪接因子。© 2024。作者。
Indexing techniques relying on k-mers have proven effective in searching for RNA sequences across thousands of RNA-seq libraries, but without enabling direct RNA quantification. We show here that arbitrary RNA sequences can be quantified in seconds through their decomposition into k-mers, with a precision akin to that of conventional RNA quantification methods. Using an index of the Cancer Cell Line Encyclopedia (CCLE) collection consisting of 1019 RNA-seq samples, we show that k-mer indexing offers a powerful means to reveal non-reference sequences, and variant RNAs induced by specific gene alterations, for instance in splicing factors.© 2024. The Author(s).