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<article xlink="http://www.w3.org/1999/xlink" dtd-version="1.0" article-type="healthcare" lang="en"><front><journal-meta><journal-id journal-id-type="publisher">IJCRR</journal-id><journal-id journal-id-type="nlm-ta">I Journ Cur Res Re</journal-id><journal-title-group><journal-title>International Journal of Current Research and Review</journal-title><abbrev-journal-title abbrev-type="pubmed">I Journ Cur Res Re</abbrev-journal-title></journal-title-group><issn pub-type="ppub">2231-2196</issn><issn pub-type="opub">0975-5241</issn><publisher><publisher-name>Radiance Research Academy</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">4404</article-id><article-id pub-id-type="doi"/><article-id pub-id-type="doi-url">http://dx.doi.org/10.31782/IJCRR.2022.14603</article-id><article-categories><subj-group subj-group-type="heading"><subject>Healthcare</subject></subj-group></article-categories><title-group><article-title>Whole Exome Sequencing Data Analysis for Detection of Breast Cancer Gene Variants and Pathway Study&#13;
</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>G</surname><given-names>Dhanyakumar</given-names></name></contrib><contrib contrib-type="author"><name><surname>Patil</surname><given-names>Maheswari L</given-names></name></contrib></contrib-group><pub-date pub-type="ppub"><day>15</day><month>03</month><year>2022</year></pub-date><volume>)</volume><issue/><fpage>17</fpage><lpage>26</lpage><permissions><copyright-statement>This article is copyright of Popeye Publishing, 2009</copyright-statement><copyright-year>2009</copyright-year><license license-type="open-access" href="http://creativecommons.org/licenses/by/4.0/"><license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0) Licence. You may share and adapt the material, but must give appropriate credit to the source, provide a link to the licence, and indicate if changes were made.</license-p></license></permissions><abstract><p>Introduction: Whole Exome Sequencing (WES) involves sequencing, analysis of protein-coding regions in genome. In present investigation, the potential gene variants were identified in human breast cancer genome using WES data analysis.&#13;
Materials and Method: The NGS data samples with accession numbers (SRR1274896_1, SRR1274896_2) and (SRR1275000_1, SRR1275000_2) were collected from ENA database. The quality of the samples was assessed by using FastQC tool and followed by aligning samples with reference genome sequence hg38 using the Bowtie2 tool. The results were retrieved in SAM format and converted to BAM format and then to sorted bam file using SAM tools, then duplicates were removed using Picard tool. Finally, Variant Calling format file was generated using BCF tools which projected the possible gene variants in the samples.&#13;
Results: The results showed variant types out of them MUC3A1 showed an average of 53 mutations, highlighting its importance as a potential gene variant observed in breast cancer. Out of nonsynonymous mutations of samples, common gene variants in samples that possess 5 and more mutations were selected. The study was carried out on pathway analysis, domain analysis, gene involvement in biological processes and gene function.&#13;
Conclusion: Majority of gene variants were involved in DNA Biosynthesis and Protein Biosynthesis and also resulted in tissue-specific location. The location of these genes showed mutated genes in cytoplasm and in nucleus indicating the impact of gene variation on intracellular process.&#13;
</p></abstract><kwd-group><kwd>Breast cancer</kwd><kwd> Mutations</kwd><kwd> MUC3A1</kwd><kwd> Next generation Sequencing (NGS)</kwd><kwd> Whole exome sequencing</kwd><kwd> MUC16</kwd></kwd-group></article-meta></front></article>
