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TEnGExA: an R package based tool for tissue enrichment and gene expression analysis.
Rawal, Hukam C; Angadi, Ulavappa; Mondal, Tapan Kumar.
Affiliation
  • Rawal HC; Indian Council of Agricultural Research (ICAR)-NIPB, New Delhi, India.
  • Angadi U; Kalasalingam University, Krishnankoil, Srivilliputtur, Tamil Nadu, India.
  • Mondal TK; ICAR-National Institute for Plant Biotechnology, LBS Centre, IARI, New Delhi 110012, India.
Brief Bioinform ; 22(3)2021 05 20.
Article in En | MEDLINE | ID: mdl-32960209
ABSTRACT
RNA-seq data analysis with rapidly advancing high-throughput sequencing technology, nowadays provides large number of transcripts or genes to perform downstream analysis including functional annotation and pathway analysis. However for the data from multiple tissues, downstream analysis with tissue-specific or tissue-enriched transcripts is highly preferable. However, there is still a need of tool for quickly performing tissue-enrichment and gene expression analysis irrespective of number of input genes or tissues at various fragments per kilobase of transcript per million fragments mapped (FPKM) thresholds. To fulfill this need, we presented a freely available R package and web-interface tool, TEnGExA, which allows tissue-enrichment analysis (TEA) for any number of genes or transcripts for any species provided only a read-count or FPKM-value matrix as input. Based on the different FPKM value and fold thresholds, TEnGExA classifies the user provided gene lists into tissue-enriched or tissue-specific transcripts along with other standard classes. By analyzing the published sample data from human, plant and microorganism, we signifies that TEnGExA can easily handle complex or large data from any species to provided tissue-enriched gene list for downstream analysis in quick time. In summary, TEnGExA is quick, easy to use and an efficient tool for TEA. The R package is freely available at https//github.com/ubagithub/TEnGExA/ and the GUI web interface is accessible at http//webtom.cabgrid.res.in/tissue_enrich/.
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Full text: 1 Database: MEDLINE Main subject: Algorithms / Programming Languages / Caenorhabditis elegans / Computational Biology / Gene Expression Profiling / Camellia Limits: Animals / Humans Language: En Year: 2021 Type: Article

Full text: 1 Database: MEDLINE Main subject: Algorithms / Programming Languages / Caenorhabditis elegans / Computational Biology / Gene Expression Profiling / Camellia Limits: Animals / Humans Language: En Year: 2021 Type: Article