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Improved Smart-Seq for sensitive full-length transcriptome profiling in single cells
Organism
Homo sapiens; Mus musculus
Samples
76
Type
Expression profiling by high...
Submitted
2013-07-29
Improved Smart-Seq for sensitive full-length transcriptome profiling in single cells.
Provenance — who produced it, who reused it
Linked to 6 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.
Deposited / produced by
Simone PicelliÅsa BjörklundRickard Sandberg
Reused by
- Single-cell RNA-seq transcriptome analysis of linear and circula... 2015 · 439 cites
- miARma-Seq: a comprehensive tool for miRNA, mRNA and circRNA ana... 2016 · 146 cites
- SC3-seq: a method for highly parallel and quantitative measureme... 2015 · 128 cites
3 further papers cite this accession but reuse could not be confirmed.
Deep data QC
94/100 · AStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
Data type / assay
bulk-RNA-seq
Organism
Homo sapiens
Metrics (value · how obtained)
n content pct
0
measured
pct q20 bases
98.7
measured
pct q30 bases
97.3
measured
gc content pct
43
measured
mean read length
43
measured
mean base quality
37.7
measured
adapter content pct
0.2
measured
duplication rate pct
46.45
measured
How this grade was computed
Weighted mean of 4 scored metric(s) → 94/100
The A 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.
pct q30 bases
97.3
measured
×1
100%
mean base quality
37.7
measured
×0.6
100%
adapter content pct
0.2
measured
×0.4
100%
duplication rate pct
46.45
measured
×0.4
63%
QC cost
29 s compute
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0