RNA-Seq data for AKT, BAD, ERBB2, IGF1R, RAF1 and KRAS(G12V) overexpressed samples with twelve green fluorescent protein control samples using human mammary epithelial cells
The goal was to capture the transcriptional activity due to over-expression of AKT, BAD, ERBB2, IGF1R, RAF1 and KRAS(G12V) genes .Overexpressions were validated using Western Blots. Illumina RNA-Seq technology was used to capture the downstream transcriptional activity. Reads were 101 base pairs long and single ended. An R open source package “Rsubread” was used to align and quantify the read using UCSC hg19 annotation. The integer-based gene counts were later normalized in TPM .
Provenance — who produced it, who reused it
Linked to 3 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.
- ComBat-seq: batch effect adjustment for RNA-seq count data 2020 · 1,681 cites
- Alternative empirical Bayes models for adjusting for batch effec... 2018 · 122 cites
1 further paper cites 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.