ArticleScientific data2026
Whole genome sequencing data of early- and late-onset colorectal cancer in 99 Korean patients.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.