{"id":2691,"date":"2025-06-13T15:11:23","date_gmt":"2025-06-13T12:11:23","guid":{"rendered":"https:\/\/www.kibs.co.ke\/wp\/?page_id=2691"},"modified":"2025-06-14T14:07:31","modified_gmt":"2025-06-14T11:07:31","slug":"differential-gene-expression-analysis-using-r","status":"publish","type":"page","link":"https:\/\/www.kibs.co.ke\/research\/differential-gene-expression-analysis-using-r\/","title":{"rendered":"Differential Gene Expression Analysis using R"},"content":{"rendered":"\n
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\n\n\n\nIn this course, the student gets hands-on skills on how to analyze RNA SEQ data in order to identify genes that are upregulated or downregulated. This is helpful in comparing diseased vs healthy tissues, identification of biomarkers for precision medicine and drug discovery, and understanding developmental processes. The objective of the Differential Gene Expression Analysis using R Course is to enhance the researchers\u2019 capacity to conduct world class scientific research and boost their institution\u2019s profile as a leading diagnostic and scientific center.

At the end of the Differential Gene Expression Analysis using R Course, the participant will be able to:
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\"Differential<\/figure>\n\n\n\n\nLearn the science, methods, and applications of RNASeq\n\n\n\nRetrieve data from public RNASeq databases\n\n\n\nPerform quality control of RNASeq data\n\n\n\nAlign RNASEQ datasets against a reference genome\n\n\n\nQuantify read counts for each gene\n\n\n\nPerform differential gene expression analysis using edgeR using QL F, glmQLFTest, glmTreat, tests, heat map clustering,\n\n\n\nVisualize RNASeq data using heat maps, bar plots, scatter plots, volcano plots, and Upset plots.\n\n\n\nPerform pathway analysis including gene ontology (GO) and KEGG pathway analysis and gene enrichment\n\n\n\n\n\n\n\n\nUsing the most powerful software, you will gain the latest skills in bioinformatics analysis.
\n\n\n\n\nWeb Resources – NCBI Tools,<\/a> GEO<\/a> , EMBL Expression Atlas<\/a>, GTEx<\/a>, TCGA<\/a>, Recount3<\/a>\n\n\n\nSoftware – R\n\n\n\nHPC – KENCLUST\n\n\n\nDatasets – SRA Datasets, 1,000 Genomes Project<\/a>, The Cancer Genome Atlas (TCGA)\n\n\n\n\n\n\nThis is the default Tab content. Feel free to delete it.\n\n\n\n\n\n\n\n\n\nThis is a 5-day training program covering the following topics:\n\n\n\n\nIntroduction to RNA Sequencing\n\n\n\nIntroduction to Linux commandline\n\n\n\nIntroduction to R\n\n\n\nQuality control of RNA sequences\n\n\n\nObtaining Reference datasets from NCBI\n\n\n\nBuilding the Genome Index\n\n\n\nAlignment of RNA sequences against the reference sequences\n\n\n\nQuantifying read counts for each gene\n\n\n\nDifferential Gene Expression (DGE) using edgeR\n\n\n\nDifferential Gene Expression Analysis\n\n\n\nPathway Analysis\n\n\n\nGene set enrichment analysis\n\n\n\n\n\n\n\n\nThe course is ideal for students and researchers working in the pharma, biotech, and medical industries. The following terms and conditions apply.\n\n\n\n\n
Minimum Entry Requirements: a bachelor\u2019s degree in bioinformatics, genetics, molecular biology, biomedical science, microbiology or any related field. Basic knowledge of the Linux commandline and R is useful but not mandatory.\n\n\n\nEmail: training@kibs.co.ke for fee inquiry or fill the contact form in the \u201cEnroll\u201d button\n\n\n\n\n\n\n\n\nKindly fill the form details below to register for your course of interest.\n\n\n\n
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Short Courses<\/h2>\n\n\n\n\nBioinformatics 1 Course<\/a>\n\n\n\nComputer-Aided Drug Design Course<\/a>\n\n\n\nCRISPR-Cas POC Diagnostics <\/a>Course<\/a>\n\n\n\nGenome Editing using CRISPR-Cas Course<\/a>\n\n\n\nMetab<\/a>olomics<\/a>\n\n\n\nMetagenomics<\/a>\n\n\n\nNex<\/a>tGen Sequencing (NGS) Data Analysis<\/a>\n\n\n\nPCR Boot Camp<\/a>\n\n\n\nPerl Programming for Bio Scientists<\/a>\n\n\n\nPython Programming for Bio Scientists<\/a>\n\n\n\nNanopore Sequencing & Data Analysis Techniques<\/a>\n\n<\/div>\n<\/div>\n\n\n\n

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