Expression data from primary colorectal cancers
Samples were taken from colorectal cancers in surgically resected specimens in 155 colorectal cancer patients. The expression profiles were determined using Affymetrix Human Genome U133Plus 2.0 arrays. Our MSI/MSS classifier was applied to these samples.
Provenance — who produced it, who reused it
Linked to 47 papers in the literature. Roles are inferred factual signals (who deposited the data vs who reused it), with counts — never a judgement about any author.
- The consensus molecular subtypes of colorectal cancer 2015 · 5,246 cites
- Gene Expression Classification of Colon Cancer into Molecular Su... 2013 · 1,541 cites
- Spatially organized multicellular immune hubs in human colorecta... 2021 · 810 cites
- LncRNA SATB2-AS1 inhibits tumor metastasis and affects the tumor... 2019 · 338 cites
- Cross-talk of four types of RNA modification writers defines tum... 2021 · 268 cites
- DeepCC: a novel deep learning-based framework for cancer molecul... 2019 · 234 cites
- Prognostic genome and transcriptome signatures in colorectal can... 2024 · 134 cites
- Conservation of immune gene signatures in solid tumors and progn... 2016 · 126 cites
- PreMSIm: An R package for predicting microsatellite instability... 2020 · 114 cites
- Unequal prognostic potentials of p53 gain-of-function mutations... 2014 · 97 cites
- An integrative analysis reveals functional targets of GATA6 tran... 2013 · 81 cites
36 further papers cite this accession but reuse could not be confirmed.
Deep data QC
metadata only · no data-level QC for this typeStandardized, field-standard QC computed by touching the data — every metric states how it was obtained
No quantitative QC rubric exists for this data type yet, so it is deliberately left unscored — this is an honest "not applicable", not a poor rating.
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0 · provisional — verify independently
Scientific quality
Based on hands-on reproduction of the papers that use this dataset. A reproducible paper that stands on this data is positive evidence; a flagged one is a prompt to look closer — never a verdict on the dataset itself without the evidence.