Refined RIP-seq protocol for epitranscriptome analysis with low input materials
We optimized the key parameters of m6A MeRIP-seq, including the starting amount of RNA, RNA fragmentation, antibody selection, MeRIP washing/elution conditions, methods for RNA library construction and the bioinformatics analysis pipeline. With the optimized immunoprecipitation conditions and a post-amplification rRNA depletion strategy, we were able to profile the m6A epitranscriptome using 2 µg of total RNA. We identified ~12,000 m6A peaks with a high signal/noise ratio from two lung adenocarc...
Provenance — who produced it, who reused it
Linked to 1 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.
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