TY - JOUR
T1 - RgnTX
T2 - Colocalization analysis of transcriptome elements in the presence of isoform heterogeneity and ambiguity
AU - Wang, Yue
AU - Wei, Zhen
AU - Su, Jionglong
AU - Coenen, Frans
AU - Meng, Jia
N1 - Funding Information:
The work was supported by the National Natural Science Foundation of China [ 32100519 and 31671373 ] and the XJTLU Key Program Special Fund [ KSF-E-51 and KSF-P-02 ].
Publisher Copyright:
© 2023 The Authors
PY - 2023
Y1 - 2023
N2 - Colocalization analysis of genomic region sets has been widely adopted to unveil potential functional interactions between corresponding biological attributes, which often serves as the basis for further investigation. A number of methods have been developed for colocalization analysis of genomic elements. However, none of them explicitly considered the transcriptome heterogeneity and isoform ambiguity, making them less appropriate for analyzing transcriptome elements. Here, we developed RgnTX, an R/Bioconductor tool for the colocalization analysis of transcriptome elements with permutation tests. Different from existing approaches, RgnTX directly takes advantage of transcriptome annotation, and offers high flexibility in the null model to simulate realistic transcriptome-wide background, such as the complex alternative splicing patterns. Importantly, it supports the testing of transcriptome elements without clear isoform association, which is often the real scenario due to technical limitations. Proposed package offers a wide selection of pre-defined functions, easy to be utilized by users for visualizing permutation results, calculating shifted z-scores and conducting multiple hypothesis testing under Benjamini-Hochberg correction. Moreover, with synthetic and real datasets, we show that RgnTX novel testing modes return distinct and more significant results compared to existing genome-based methods. We believe RgnTX should make a useful tool to characterize the randomness of the transcriptome, and for conducting statistical association analysis for genomic region sets within the heterogeneous transcriptome. The package now has been accepted by Bioconductor and is freely available at: https://bioconductor.org/packages/RgnTX.
AB - Colocalization analysis of genomic region sets has been widely adopted to unveil potential functional interactions between corresponding biological attributes, which often serves as the basis for further investigation. A number of methods have been developed for colocalization analysis of genomic elements. However, none of them explicitly considered the transcriptome heterogeneity and isoform ambiguity, making them less appropriate for analyzing transcriptome elements. Here, we developed RgnTX, an R/Bioconductor tool for the colocalization analysis of transcriptome elements with permutation tests. Different from existing approaches, RgnTX directly takes advantage of transcriptome annotation, and offers high flexibility in the null model to simulate realistic transcriptome-wide background, such as the complex alternative splicing patterns. Importantly, it supports the testing of transcriptome elements without clear isoform association, which is often the real scenario due to technical limitations. Proposed package offers a wide selection of pre-defined functions, easy to be utilized by users for visualizing permutation results, calculating shifted z-scores and conducting multiple hypothesis testing under Benjamini-Hochberg correction. Moreover, with synthetic and real datasets, we show that RgnTX novel testing modes return distinct and more significant results compared to existing genome-based methods. We believe RgnTX should make a useful tool to characterize the randomness of the transcriptome, and for conducting statistical association analysis for genomic region sets within the heterogeneous transcriptome. The package now has been accepted by Bioconductor and is freely available at: https://bioconductor.org/packages/RgnTX.
KW - Colocalization analysis
KW - Isoform ambiguity
KW - Multiple hypothesis testing
KW - Permutation test
KW - RNA methylations
KW - Transcriptome
UR - http://www.scopus.com/inward/record.url?scp=85169466606&partnerID=8YFLogxK
U2 - 10.1016/j.csbj.2023.08.021
DO - 10.1016/j.csbj.2023.08.021
M3 - Article
AN - SCOPUS:85169466606
SN - 2001-0370
VL - 21
SP - 4110
EP - 4117
JO - Computational and Structural Biotechnology Journal
JF - Computational and Structural Biotechnology Journal
ER -