Evidence map›Paper›PMID 31830035›Full record

ArticlePLoS computational biology2019

Molecular sampling at logarithmic rates for next-generation sequencing.

Caroline Horn, Julia Salzman

Abstract read
In one paragraph

Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Caroline HornDepartment of Biochemistry, Stanford University, Stanford, California, United States of America.ORCID 0000-0003-2863-709X
Julia SalzmanDepartment of Biochemistry, Stanford University, Stanford, California, United States of America.ORCID 0000-0001-7630-3436

Funding

Unbiased discovery of mechanisms regulating circRNAR01GM116847 · NIGMS · STANFORD UNIVERSITY · PI SALZMAN, JULIA · 2015 to 2019
$1.6M
NIGMS NIH HHS R01 GM116847
6 · The paper itself

Abstract

Next-generation sequencing is a cutting edge technology, but to quantify a dynamic range of abundances for different RNA or DNA species requires increasing sampling depth to levels that can be prohibitively expensive due to physical limits on molecular throughput of sequencers. To overcome this problem, we introduce a new general sampling theory which uses biophysical principles to functionally encode the abundance of a species before sampling, SeQUential depletIon and enriCHment (SQUICH). In theory and simulation, SQUICH enables sampling at a logarithmic rate to achieve the same precision as attained with conventional sequencing. A simple proof of principle experimental implementation of SQUICH in a controlled complex system of ~262,000 oligonucleotides already reduces sequencing depth by a factor of 10. SQUICH lays the groundwork for a general solution to a fundamental problem in molecular sampling and enables a new generation of efficient, precise molecular measurement at logarithmic or better sampling depth.

Indexed as

Base SequenceComputational BiologyComputer SimulationDNAHigh-Throughput Nucleotide SequencingProof of Concept StudyRNASampling StudiesSequence Analysis, DNASequence Analysis, RNASpecies SpecificityDNARNA

Identifiers

PMID31830035
PMCPMC6932819

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.