Accession numbers, mapping statistics, and matched RNA accession numbers for 99 Korean CRC whole-genome samples

Kim, Jae-Yoon;Jin Ha, Ye;Park, Seung-Jin;Lee, Sun-Woo;Kim, Seon-Yeop;Oh, Seung-Eun;Park, Jong-Lyul;Tak, Ka Hee;Sik Yoon, Yong;Lyul Lee, Jong;Kim, Seon-Young;Kim, Chan Wook

Description

We performed whole-genome sequencing (WGS) on 99 Korean patients with early- and late-onset colorectal cancer (CRC). This dataset provides the accession numbers, mapping statistics, and matched RNA accession numbers for the deposited whole-genome data of these 99 patients. The abstract of our paper is as follows: Colorectal cancer (CRC) is the third most prevalent cancer type worldwide. Despite improvements in screening programs, the incidence of early-onset CRC (EOCRC) in patients under 50 years old is rapidly increasing, including in Korea, in contrast to the decreasing trend of late-onset CRC (LOCRC). However, a comprehensive biological understanding of CRC’s coding and non-coding variants, onset-dependent prognostic variables, and the genetic and transcriptomic differences between EOCRC and LOCRC remains limited. To provide insights into this, we present a high-quality multi-omics dataset consisting of whole genome sequencing (WGS) and RNA sequencing (RNA-seq) data from 49 EOCRC and 50 LOCRC patients. WGS was performed using the DNBSEQ-T7 platform, generating 1.409 billion reads at an average depth of 37.70×. RNA-seq data previously generated from the same samples are included to support integrative analysis. This dataset enables comprehensive exploration of genomic and transcriptomic alterations in CRC and serves as a valuable resource for identifying onset-specific biomarkers and molecular features, ultimately supporting improved diagnosis and therapeutic strategies.

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Mentions (0)

Metrics

Dataset Index

2.0

FAIR Score

88%

Citations

4

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

figshare

License

Creative Commons Attribution 4.0 International

Assigned Domain

Subfield

Molecular Biology

Field

Biochemistry, Genetics and Molecular Biology

Domain

Life Sciences

Confidence Score

51%

Source

Scholar Data Model

Keywords

Genomics and transcriptomics

Normalization Factors

FT

53.85

CTw

1.00

MTw

1.00