re-Searcher: GUI-based bioinformatics tool for simplified genomics data mining of VCF files

Karabayev, Daniyar; Molkenov, Askhat; Yerulanuly, Kaiyrgali; Kabimoldayev, Ilyas; Daniyarov, Asset; Sharip, Aigul; Seisenova, Ainur; Zhumadilov, Zhaxybay; Kairov, Ulykbek

doi:10.7717/peerj.11333

Cited by 5 publications

(3 citation statements)

References 16 publications

(17 reference statements)

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“…We compared the main features in SCI-VCF with the existing open-source tools VIVA ( 10 ), vcfR ( 11 ), vcflib ( 12 ), CuteVariant ( 19 ), re-Searcher ( 20 ), VCF-Miner ( 21 ), VCFtools ( 9 ) and GEMINI ( 22 ). The results are detailed in Table 1 .…”

Section: Resultsmentioning

confidence: 99%

SCI-VCF: a cross-platform GUI solution to summarize, compare, inspect and visualize the variant call format

Kamaraj,

Sinha

2024

NAR Genomics and Bioinformatics

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As genomics advances swiftly and its applications extend to diverse fields, bioinformatics tools must enable researchers and clinicians to work with genomic data irrespective of their programming expertise. We developed SCI-VCF, a Shiny-based comprehensive analysis utility to summarize, compare, inspect, analyse and design interactive visualizations of the genetic variants from the variant call format. With an intuitive graphical user interface, SCI-VCF aims to bridge the approachability gap in genomics that arises from the existing predominantly command-line utilities. SCI-VCF is written in R and is freely available at https://doi.org/10.5281/zenodo.11453080. For installation-free access, users can avail themselves of an online version at https://ibse.shinyapps.io/sci-vcf-online.

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Section: Resultsmentioning

confidence: 99%

SCI-VCF: a cross-platform GUI solution to summarize, compare, inspect and visualize the variant call format

Kamaraj,

Sinha

2024

NAR Genomics and Bioinformatics

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“…The SNPs were annotated with SnpEff v.5.1 (Cingolani et al, 2012a). Where necessary, the annotated SNP file was further processed (e.g., filtering for intergenic SNPs or significant SNPs from the association analyses (see below)) with SnpSift v.5.1 (Cingolani et al, 2012b) or re‐Searcher v.1.0 (Karabayev et al, 2021). The function of significant SNPs that were identified by the different association analyses (see below) was determined with tbg‐tools v.0.2 (Schönnenbeck et al, 2021).…”

Section: Methodsmentioning

confidence: 99%

“…with SnpSift v.5.1 (Cingolani et al, 2012b) or re-Searcher v.1.0 (Karabayev et al, 2021). The function of significant SNPs that were identified by the different association analyses (see below) was determined with tbg-tools v.0.2 (Schönnenbeck et al, 2021).…”

Section: Dna Extraction Genotyping By Sequencing and Snp Identificationmentioning

confidence: 99%

A genome‐wide genetic association study reveals SNPs significantly associated with environmental variables and specific leaf area in European beech

Müller,

Leuschner,

Weithmann

et al. 2024

Physiologia Plantarum

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European beech is negatively affected by climate change and a further growth decline is predicted for large parts of its distribution range. Despite the importance of this species, little is known about its genetic adaptation and especially the genetic basis of its physiological traits. Here, we used genotyping by sequencing to identify SNPs in 43 German European beech populations growing under different environmental conditions. In total, 28 of these populations were located along a precipitation and temperature gradient in northern Germany, and single tree‐based hydraulic and morphological traits were available. We obtained a set of 13,493 high‐quality SNPs that were used for environmental and SNP‐trait association analysis. In total, 22 SNPs were identified that were significantly associated with environmental variables or specific leaf area (SLA). Several SNPs were located in genes related to stress response. The majority of the significant SNPs were located in non‐coding (intergenic and intronic) regions. These may be in linkage disequilibrium with the causative coding or regulatory regions. Our study gives insights into the genetic basis of abiotic adaptation in European beech, and provides genetic resources that can be used in future studies on this species. Besides clear patterns of local adaptation to environmental conditions of the investigated populations, the analyzed morphological and hydraulic traits explained most of the explainable genetic variation. Thus, they could successfully be altered in tree breeding programs, which may help to increase the adaptation of European beech to changing environmental conditions in the future.

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GAMUT: A genomics big data management tool

et al. 2021

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re-Searcher: GUI-based bioinformatics tool for simplified genomics data mining of VCF files

Cited by 5 publications

References 16 publications

SCI-VCF: a cross-platform GUI solution to summarize, compare, inspect and visualize the variant call format

SCI-VCF: a cross-platform GUI solution to summarize, compare, inspect and visualize the variant call format

A genome‐wide genetic association study reveals SNPs significantly associated with environmental variables and specific leaf area in European beech

GAMUT: A genomics big data management tool

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