Evidence map›Paper›PMID 24090499›Full record

ArticleBMC genomics2013

InsertionMapper: a pipeline tool for the identification of targeted sequences from multidimensional high throughput sequencing data.

Wenwei Xiong, Limei He, Yubin Li, Hugo K Dooner, Chunguang Du

Abstract read
In one paragraph

Article in BMC genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Spontaneous mutations in maize pollen are frequent in some lines and arise mainly from retrotranspositions and deletions.Proceedings of the National Academy of Sciences of the United States of America · 2019
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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Wenwei XiongDepartment of Biology and Molecular Biology, Montclair State University, Montclair, NJ 07043, USA. duc@mail.montclair.edu.
Limei He
Yubin Li
Hugo K Dooner
Chunguang Du

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe advent of next-generation high-throughput technologies has revolutionized whole genome sequencing, yet some experiments require sequencing only of targeted regions of the genome from a very large number of samples. These regions can be amplified by PCR and sequenced by next-generation methods using a multidimensional pooling strategy. However, there is at present no available generalized tool for the computational analysis of target-enriched NGS data from multidimensional pools.

resultsHere we present InsertionMapper, a pipeline tool for the identification of targeted sequences from multidimensional high throughput sequencing data. InsertionMapper consists of four independently working modules: Data Preprocessing, Database Modeling, Dimension Deconvolution and Element Mapping. We illustrate InsertionMapper with an example from our project 'New reverse genetics resources for maize', which aims to sequence-index a collection of 15,000 independent insertion sites of the transposon Ds in maize. Identified sequences are validated by PCR assays. This pipeline tool is applicable to similar scenarios requiring analysis of the tremendous output of short reads produced in NGS sequencing experiments of targeted genome sequences.

conclusionsInsertionMapper is proven efficacious for the identification of target-enriched sequences from multidimensional high throughput sequencing data. With adjustable parameters and experiment configurations, this tool can save great computational effort to biologists interested in identifying their sequences of interest within the huge output of modern DNA sequencers. InsertionMapper is freely accessible at https://sourceforge.net/p/insertionmapper and http://bo.csam.montclair.edu/du/insertionmapper.

Indexed as

SoftwareBase SequenceComputational BiologyDNA Transposable ElementsGenome, PlantHigh-Throughput Nucleotide SequencingPolymerase Chain ReactionReproducibility of ResultsZea maysDNA Transposable Elements

Identifiers

PMID24090499
PMCPMC3850689

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LicenceCC BY
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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.