Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Exhaustive Capture of Ovarian Cancer Transcriptional and Genomic Variant Integrating Canonical and Mapping-Free Protocols

Version 1 : Received: 17 December 2020 / Approved: 18 December 2020 / Online: 18 December 2020 (15:15:50 CET)

How to cite: Fu, Z.; Lu, C.; Ding, C.; Zhou, C.; Yu, T.; Yang, Y.; Shi, L. Exhaustive Capture of Ovarian Cancer Transcriptional and Genomic Variant Integrating Canonical and Mapping-Free Protocols. Preprints 2020, 2020120476 (doi: 10.20944/preprints202012.0476.v1). Fu, Z.; Lu, C.; Ding, C.; Zhou, C.; Yu, T.; Yang, Y.; Shi, L. Exhaustive Capture of Ovarian Cancer Transcriptional and Genomic Variant Integrating Canonical and Mapping-Free Protocols. Preprints 2020, 2020120476 (doi: 10.20944/preprints202012.0476.v1).

Abstract

Ovarian cancer is the most frequent cause of deaths in gynecologic malignancies. Many possible mechanisms have been proposed via RNAseq and DNAseq technique recently. However, the driving factors are still obscure. The possible reasons are attributed to the incomplete human reference. This study integrated the canonical mapping-based and mapping-free protocols to extract reliable variations and novel events. We eventually obtained 450 reliable SNVs from the WES data and novel events from the RNAseq data, including 154 SNVs, 462 intron events, two repeats and six splice events. We identified six differentially expressed genes and six contigs that are significantly related to survival prognosis. The recurrent SNVs in significantly differentially expressed genes can be validated in an independent cohort of 20 Chinese ovarian cancer patients.

Subject Areas

Ovarian cancer; mapping-based; mapping-free; SNVs; survival prognosis

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