Differential expression of human tRNA genes drives the abundance of tRNA-derived fragments
The human genome encodes hundreds of tRNA genes but their individual contribution to the tRNA pool is not fully understood. Deep sequencing of tRNA transcripts (tRNA-Seq) can estimate tRNA abundance at single gene resolution, but tRNA structures and post-transcriptional modifications impair these analyses. Here we present a bioinformatics strategy to investigate differential tRNA gene expression and use it to compare tRNA-Seq datasets from cultured human cells and human brain. We find that seque...
Provenance — who produced it, who reused it
Linked to 2 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.
1 further paper cites this accession but reuse could not be confirmed.
Deep data QC
67/100 · DStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
The D 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