Differential Gene Expression Analysis of Non-Small Cell Lung Cancer Samples to Classify Candidate Genes
Differential gene expression is an analysis of gene data, in which the RNA sequence data after next-generation sequencing are to be visualized for any quantitative changes in the levels of the experimental data set. This work aims to derive the transcript statistics on a gene transcript file with a...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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D. G. Pylarinos
2023-04-01
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| Series: | Engineering, Technology & Applied Science Research |
| Subjects: | |
| Online Access: | https://etasr.com/index.php/ETASR/article/view/5770 |
| _version_ | 1797695411717144576 |
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| author | Neelambika B. Hiremath Pruthviraja Dayananda |
| author_facet | Neelambika B. Hiremath Pruthviraja Dayananda |
| author_sort | Neelambika B. Hiremath |
| collection | DOAJ |
| description |
Differential gene expression is an analysis of gene data, in which the RNA sequence data after next-generation sequencing are to be visualized for any quantitative changes in the levels of the experimental data set. This work aims to derive the transcript statistics on a gene transcript file with a fold change of genes on a normalized scale, in order to identify quantitative changes in gene expression of the difference between the reference genome and Non-Small Cell Lung Cancer (NSCLC) samples. This insight makes a clinical impact in assessing and characterizing candidate genes. The pipeline comprises tuxedo protocol and programming language R with the standard ballgown package. The resultant data set and the plot displays depict the candidate genes in their respective location which are significant in expressing their changes in NSCLC samples. The samples are compared with prominent gene labels of NSCLC samples. The results explain the differential expression of particular samples across samples from both genders.
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| first_indexed | 2024-03-12T03:12:03Z |
| format | Article |
| id | doaj.art-3a1fcd5033c745e7bdf77c13a65f3b41 |
| institution | Directory Open Access Journal |
| issn | 2241-4487 1792-8036 |
| language | English |
| last_indexed | 2024-03-12T03:12:03Z |
| publishDate | 2023-04-01 |
| publisher | D. G. Pylarinos |
| record_format | Article |
| series | Engineering, Technology & Applied Science Research |
| spelling | doaj.art-3a1fcd5033c745e7bdf77c13a65f3b412023-09-03T14:19:51ZengD. G. PylarinosEngineering, Technology & Applied Science Research2241-44871792-80362023-04-0113210.48084/etasr.5770Differential Gene Expression Analysis of Non-Small Cell Lung Cancer Samples to Classify Candidate GenesNeelambika B. Hiremath0Pruthviraja Dayananda1Department of Computer Science and Engineering, JSS Academy of Technical Education, IndiaDepartment of Information Science and Engineering, JSS Academy of Technical Education, India Differential gene expression is an analysis of gene data, in which the RNA sequence data after next-generation sequencing are to be visualized for any quantitative changes in the levels of the experimental data set. This work aims to derive the transcript statistics on a gene transcript file with a fold change of genes on a normalized scale, in order to identify quantitative changes in gene expression of the difference between the reference genome and Non-Small Cell Lung Cancer (NSCLC) samples. This insight makes a clinical impact in assessing and characterizing candidate genes. The pipeline comprises tuxedo protocol and programming language R with the standard ballgown package. The resultant data set and the plot displays depict the candidate genes in their respective location which are significant in expressing their changes in NSCLC samples. The samples are compared with prominent gene labels of NSCLC samples. The results explain the differential expression of particular samples across samples from both genders. https://etasr.com/index.php/ETASR/article/view/5770differential gene expressionRNA sequencemachine learningnon-small cell lung cancerclassificationnext-generation sequencing |
| spellingShingle | Neelambika B. Hiremath Pruthviraja Dayananda Differential Gene Expression Analysis of Non-Small Cell Lung Cancer Samples to Classify Candidate Genes Engineering, Technology & Applied Science Research differential gene expression RNA sequence machine learning non-small cell lung cancer classification next-generation sequencing |
| title | Differential Gene Expression Analysis of Non-Small Cell Lung Cancer Samples to Classify Candidate Genes |
| title_full | Differential Gene Expression Analysis of Non-Small Cell Lung Cancer Samples to Classify Candidate Genes |
| title_fullStr | Differential Gene Expression Analysis of Non-Small Cell Lung Cancer Samples to Classify Candidate Genes |
| title_full_unstemmed | Differential Gene Expression Analysis of Non-Small Cell Lung Cancer Samples to Classify Candidate Genes |
| title_short | Differential Gene Expression Analysis of Non-Small Cell Lung Cancer Samples to Classify Candidate Genes |
| title_sort | differential gene expression analysis of non small cell lung cancer samples to classify candidate genes |
| topic | differential gene expression RNA sequence machine learning non-small cell lung cancer classification next-generation sequencing |
| url | https://etasr.com/index.php/ETASR/article/view/5770 |
| work_keys_str_mv | AT neelambikabhiremath differentialgeneexpressionanalysisofnonsmallcelllungcancersamplestoclassifycandidategenes AT pruthvirajadayananda differentialgeneexpressionanalysisofnonsmallcelllungcancersamplestoclassifycandidategenes |