Evidence map›Paper›PMID 30258547›Full record

ArticleComputational and structural biotechnology journal2018

SEG - A Software Program for Finding Somatic Copy Number Alterations in Whole Genome Sequencing Data of Cancer.

Mucheng Zhang, Deli Liu, Jie Tang, Yuan Feng, Tianfang Wang, Kevin K Dobbin, Paul Schliekelman, Shaying Zhao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Computational and structural biotechnology journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Identification of Copy Number Alterations from Next-Generation Sequencing Data.Advances in experimental medicine and biology · 2022
    Article
  4. 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

8 authors.

Mucheng ZhangDepartment of Biochemistry and Molecular Biology, Institute of Bioinformatics, University of Georgia, Athens, GA30602-7229, USA.
Deli LiuDepartment of Biochemistry and Molecular Biology, Institute of Bioinformatics, University of Georgia, Athens, GA30602-7229, USA.
Jie TangDepartment of Biochemistry and Molecular Biology, Institute of Bioinformatics, University of Georgia, Athens, GA30602-7229, USA.
Yuan FengDepartment of Biochemistry and Molecular Biology, Institute of Bioinformatics, University of Georgia, Athens, GA30602-7229, USA.
Tianfang WangDepartment of Biochemistry and Molecular Biology, Institute of Bioinformatics, University of Georgia, Athens, GA30602-7229, USA.
Kevin K DobbinDepartment of Biostatistics, University of Georgia, Athens, GA30602-7229, USA.
Paul SchliekelmanDepartment of Statistics, University of Georgia, Athens, GA30602-7229, USA.
Shaying ZhaoDepartment of Biochemistry and Molecular Biology, Institute of Bioinformatics, University of Georgia, Athens, GA30602-7229, USA.

Funding

Man's Best Friend for Driver-Passenger DistinctionR01CA182093 · NCI · UNIVERSITY OF GEORGIA · PI ZHAO, SHAYING · 2014 to 2018
$1.6M
NCI NIH HHS R01 CA182093
6 · The paper itself

Abstract

As next-generation sequencing technology advances and the cost decreases, whole genome sequencing (WGS) has become the preferred platform for the identification of somatic copy number alteration (CNA) events in cancer genomes. To more effectively decipher these massive sequencing data, we developed a software program named SEG, shortened from the word "segment". SEG utilizes mapped read or fragment density for CNA discovery. To reduce CNA artifacts arisen from sequencing and mapping biases, SEG first normalizes the data by taking the log

Indexed as

CancerSEGSomatic Copy Number AlterationWhole Genome Sequencing

Identifiers

PMID30258547
PMCPMC6154469

What OpenQuestion holds

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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.