High-throughput sequencing of matched colorectal normal, tumor and metastasis tissues and proof-of principal bioinformatics modeling of therapeutic consequences of miRNA applications
MiRNAs are discussed as diagnostic and therapeutic molecules. However, effective miRNA drug treatments with miRNAs are so far hampered by the complexity of the miRNA networks. To identify potential miRNA drugs in colorectal cancer, we profiled miRNA and mRNA expression in matching normal, tumor and metastasis tissues of eight patients by Illumina sequencing. We identified miRNA-1 as top candidate differentially expressed in tumor and metastasis. Furthermore, miRNA-1 was de-regulated in 16 additi...
Provenance — who produced it, who reused it
Linked to 10 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.
- Noncoding Effects of Circular RNA CCDC66 Promote Colon Cancer Gr... 2017 · 740 cites
- sRNAnalyzer—a flexible and customizable small RNA sequencing dat... 2017 · 93 cites
- Host gene constraints and genomic context impact the expression... 2016 · 84 cites
7 further papers cite this accession but reuse could not be confirmed.
Deep data QC
58/100 · FStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
Bulk RNA-seq (Homo sapiens, mixed assays). F grade, do not reuse. Critically high N-content (35.854%) and poor base quality (Q30=60.2%) indicate catastrophic sequencing failure or contamination; data cannot support reliable expression profiling.
The F grade is a transparent weighted average. Each metric below scored from 0–100% against the published bulk-RNA-seq thresholds, weighted by its importance; nothing is hidden or subjective.
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0
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.