Comprehensive molecular characterization of human colon and rectal cancer
Comprehensive molecular characterization of human colon and rectal cancer is a dataset published in Nature (2012). On theSindex it has a DataRank of 19.2, placing it in the top 6.1% of the data-sharing corpus. It has been cited 8,620 times, with 200 citing works in its 1-hop citation network. Its calibrated FAIR score is 53/100.
Abstract
To characterize somatic alterations in colorectal carcinoma, we conducted a genome-scale analysis of 276 samples, analysing exome sequence, DNA copy number, promoter methylation and messenger RNA and microRNA expression. A subset of these samples (97) underwent low-depth-of-coverage whole-genome sequencing. In total, 16% of colorectal carcinomas were found to be hypermutated: three-quarters of these had the expected high microsatellite instability, usually with hypermethylation and MLH1 silencing, and one-quarter had somatic mismatch-repair gene and polymerase ε (POLE) mutations. Excluding the hypermutated cancers, colon and rectum cancers were found to have considerably similar patterns of genomic alteration. Twenty-four genes were significantly mutated, and in addition to the expected APC, TP53, SMAD4, PIK3CA and KRAS mutations, we found frequent mutations in ARID1A, SOX9 and FAM123B. Recurrent copy-number alterations include potentially drug-targetable amplifications of ERBB2 and newly discovered amplification of IGF2. Recurrent chromosomal translocations include the fusion of NAV2 and WNT pathway member TCF7L1. Integrative analyses suggest new markers for aggressive colorectal carcinoma and an important role for MYC-directed transcriptional activation and repression.
›Data sources & pipeline
FAIR Checklist
Context only (not used in score)- Has DOI
- Indexed in repositories
- Open Access
- DataCite relations
- Linked datasets
- Dataset classification
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →
DataRank Breakdown
Base Score Contribution
1.4
From this paper's citation signal
Citation Network Contribution
17.8
From 200 citing papers with measurable signal
Top 5 citers driving the network score
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
- The Cancer Genome Atlas Pan-Cancer analysis projectNature Genetics20139,117 citationsDataRank 1.4Top 39%
- Integrated genomic analyses of ovarian carcinomaNature20118,094 citationsDataRank 1.3
- Comprehensive genomic characterization defines human glioblastoma genes and core pathwaysNature20087,782 citationsDataRank 23.2Top 3%
- UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival AnalysesNeoplasia20176,502 citationsDataRank 16.6Top 10%
- Oncogenic Signaling Pathways in The Cancer Genome AtlasCell20183,322 citationsDataRank 1.2
Why this DataRank?
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 7% comes from its base citations and 93% from the citation network (200 citing papers contributed measurable signal).
- Base score B(p)
- log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
- Network N(p)
- Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
- Damping factor d = 0.85
- DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
- Self-citations excluded
- Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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