RT Journal Article
SR Electronic
T1 NanoTrans: an integrated computational framework for comprehensive transcriptome analyses with Nanopore direct-RNA sequencing
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2022.11.29.518309
DO 10.1101/2022.11.29.518309
A1 Fan Wang
A1 Xinxin Zhang
A1 Li Zhang
A1 Jing Li
A1 Jia-Xing Yue
YR 2022
UL http://biorxiv.org/content/early/2022/12/01/2022.11.29.518309.abstract
AB Summary Nanopore direct-RNA sequencing (DRS) provides the direct access to native RNA strands with full-length information, shedding light on rich qualitative and quantitative properties of gene expression profiles. Here with NanoTrans, we present an integrated computational framework that comprehensively covers all major DRS-based application scopes, including isoform clustering and quantification, poly(A) tail length estimation, RNA modification profiling, and fusion gene detection. In addition to its merit in providing such a streamlined one-stop solution, NanoTrans also shines in its workflow-orientated modular design, batch processing capability, rich tabular and graphic report outputs, as well as automatic installation and configuration support. Finally, by applying NanoTrans to real DRS datasets of yeast, Arabidopsis, as well as human embryonic kidney and cancer cell lines, we further demonstrated its utility, effectiveness, and efficacy across a wide range of DRS-based application settings.Availability and implementation NanoTrans is written in bash, Perl, and R. It is free for use under the MIT license, available at https://github.com/yjx1217/NanoTrans. The key raw data are uploaded to the Research Deposit public platform (www.researchdata.org.cn), with the approval RDD number of RDDXXXXXXXXXXXX.Contact zhangli{at}sysucc.org.cn; lijing3{at}sysucc.org.cn; yuejiaxing{at}gmail.comSupplementary information Supplementary data are available at Bioinformatics online.Competing Interest StatementThe authors have declared no competing interest.