NDLI: TED toolkit: a comprehensive approach for convenient transcriptomic profiling as a clinically-oriented application

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TED toolkit: a comprehensive approach for convenient transcriptomic profiling as a clinically-oriented application

Content Provider	Semantic Scholar
Author	Ali, Thahmina Kim, Baekdoo Lijeron, Carlos Ogunwobi, Olorunseun O. Mazumder, Raja Krampis, Konstantinos
Copyright Year	2017
Abstract	In translational medicine, the technology of RNA sequencing (RNA-seq) continues to prove powerful, and transforming the RNA-seq data into biological insights has become increasingly imperative. We present the Transcriptomics profiler for Easy Discovery (TED) toolkit, a comprehensive approach to processing and analyzing RNA-seq data. TED is divided into three major modules: data quality control, transcriptome data analysis, and data discovery, with eleven pipelines in total. These pipelines perform the preliminary steps from assessing and correcting the quality of the RNA-seq data, to the simultaneous analysis of five transcriptomic features (differentially expressed coding, non-coding, novel isoform genes, gene fusions, alternative splicing events, genetic variants of somatic and germline mutations) and ultimately translating the RNA-seq analysis findings into actionable, clinically-relevant reports. TED was evaluated using previously published prostate cancer transcriptome data where we observed previously studied outcomes, and also created a knowledge database of highly-integrated, biologically relevant reports demonstrating that it is well-positioned for clinical applications. TED is implemented on an instance of the Galaxy platform (Galaxy page: http://galaxy.hunter.cuny.edu/u/bioitcore/p/transcriptomics-profiler-for-easy-discovery-ted-toolkit , Documentation Manual: http://ted.readthedocs.io/en/latest/index.html ) as intuitive and reproducible pipelines providing a manageable strategy for conducting substantial transcriptome analysis in a routine and sustainable fashion for bioinformatics researchers and clinicians alike.
File Format	PDF HTM / HTML
DOI	10.7287/peerj.preprints.3385v1
Alternate Webpage(s)	https://peerj.com/preprints/3385.pdf
Alternate Webpage(s)	https://doi.org/10.7287/peerj.preprints.3385v1
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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