Evidence map›Paper›PMID 28868335›Full record

ArticleIEEE transactions on molecular, biological, and multi-scale communications2016

Fundamental Bounds for Sequence Reconstruction from Nanopore Sequencers.

Abram Magner, Jarosław Duda, Wojciech Szpankowski, Ananth Grama

Abstract read
In one paragraph

Article in IEEE transactions on molecular, biological, and multi-scale communications, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Trace Reconstruction Problems in Computational Biology.IEEE transactions on information theory · 2021
    Article
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

4 authors.

Abram MagnerCoordinated Science Laboratory, University of Illinois at Urbana-Champaign.
Jarosław DudaDepartment of Computer Science and Center for Science of Information, Purdue University. He is now with the Institute of Computer Science, Faculty of Mathematics and Computer Science Jagiellonian University.
Wojciech SzpankowskiDepartment of Computer Science and Center for Science of Information, Purdue University. Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Poland.
Ananth GramaDepartment of Computer Science and Center for Science of Information, Purdue University.

Funding

Continued Development and Maintenance of the MG-RAST Metagenomics PipelineR01AI123037 · NIAID · PURDUE UNIVERSITY · PI GRAMA, ANANTH, MEYER, FOLKER · 2016 to 2020
$3.7M
Theoretical Foundations and Software Infrastructure for Biological Network DatabasesU01CA198941 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI KOYUTURK, MEHMET · 2015 to 2017
$1.4M
NCI NIH HHS U01 CA198941NIAID NIH HHS R01 AI123037
6 · The paper itself

Abstract

Nanopore sequencers are emerging as promising new platforms for high-throughput sequencing. As with other technologies, sequencer errors pose a major challenge for their effective use. In this paper, we present a novel information theoretic analysis of the impact of insertion-deletion (indel) errors in nanopore sequencers. In particular, we consider the following problems: (i) for given indel error characteristics and rate, what is the probability of accurate reconstruction as a function of sequence length; (ii) using replicated extrusion (the process of passing a DNA strand through the nanopore), what is the number of replicas needed to accurately reconstruct the true sequence with high probability? Our results provide a number of important insights: (i) the probability of accurate reconstruction of a sequence from a single sample in the presence of indel errors tends quickly (i.e., exponentially) to zero as the length of the sequence increases; and (ii) replicated extrusion is an effective technique for accurate reconstruction. We show that for typical distributions of indel errors, the required number of replicas is a slow function (polylogarithmic) of sequence length - implying that through replicated extrusion, we can sequence large reads using nanopore sequencers. Moreover, we show that in certain cases, the required number of replicas can be related to information-theoretic parameters of the indel error distributions.

Identifiers

PMID28868335
PMCPMC5575792

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Registered trials

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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.