Evidence map›Paper›PMID 32637866›Full record

ArticleInternational journal of reproductive biomedicine2020

Strategies for whole-exome sequencing analysis in a case series study of familial male infertility.

Masomeh Askari, Dor Mohammad Kordi Tamandani, Navid Almadani, Mehdi Totonch

Open access · goldAbstract readCase Reports
In one paragraph

Article in International journal of reproductive biomedicine, 2020. 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
0.4field-weighted citation impact, top 33% of its field
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, 2 citations in OpenAlex.

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

4 authors at 2 institutions in 1 country.

Masomeh AskariDepartment of Biology, Sistan and Baluchestan University, Zahedan, Iran.
Dor Mohammad Kordi TamandaniDepartment of Biology, Sistan and Baluchestan University, Zahedan, Iran.
Navid AlmadaniDepartment of Genetics, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, ACECR, Tehran, Iran.
Mehdi TotonchDepartment of Genetics, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, ACECR, Tehran, Iran.
Royan Institute · IRUniversity of Sistan and Baluchestan · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInfertility is one of the common health issues around the world. The prevalence of male factor infertility among infertile couples is approximately 30%-35%, of which genetic factors account for 15%. The family-based whole-exome sequencing (WES) approach can accurately detect novel variants. However, selecting an appropriate sample for data generation using WES has proven to be challenging in familial male infertility studies. The aim of this study was to identify types of pathogenic male infertility in cases of familial asthenozoospermia. CASE: Two families with multiple cases were recruited for the purpose of WES. The study population included two affected cases in pedigree I and three affected cases in pedigree II. Two different variant callers (SAMtools and GATK) with a single-sample calling strategy (SSCS) and a multiple-sample calling strategy (MSCS), were applied to identify variant sites.

conclusionIn this study, we represented the results for variant prioritization of WES data without sequencing fertile siblings in the same pedigree by applying two different pipelines (homozygosity and linkage-based strategy). Using the aforementioned strategies, we prioritized annotated variants and generated a logical shortlist of private variants for each pedigree.

Indexed as

GATKMale infertilitySAMtools.Whole-exome sequencing

Identifiers

PMID32637866
PMCPMC7306064
OpenAlexW3035582011

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.