GENI: A web server to identify gene set enrichments in tumor samples

Arata Hayashi, Shmuel Ruppo, Elisheva E. Heilbrun, Chiara Mazzoni, Sheera Adar, Moran Yassour, Areej Abu Rmaileh, Yoav D. Shaul

نتاج البحث: نشر في مجلةمقالةمراجعة النظراء

ملخص

The Cancer Genome Atlas (TCGA) and analogous projects have yielded invaluable tumor-associated genomic data. Despite several web-based platforms designed to enhance accessibility, certain analyses require prior bioinformatic expertise. To address this need, we developed Gene ENrichment Identifier (GENI, https://www.shaullab.com/geni), which is designed to promptly compute correlations for genes of interest against the entire transcriptome and rank them against well-established biological gene sets. Additionally, it generates comprehensive tables containing genes of interest and their corresponding correlation coefficients, presented in publication-quality graphs. Furthermore, GENI has the capability to analyze multiple genes simultaneously within a given gene set, elucidating their significance within a specific biological context. Overall, GENI's user-friendly interface simplifies the biological interpretation and analysis of cancer patient-associated data, advancing the understanding of cancer biology and accelerating scientific discoveries.

اللغة الأصليةإنجليزيّة أمريكيّة
الصفحات (من إلى)5531-5537
عدد الصفحات7
دوريةComputational and Structural Biotechnology Journal
مستوى الصوت21
المعرِّفات الرقمية للأشياء
حالة النشرنُشِر - يناير 2023

All Science Journal Classification (ASJC) codes

  • !!Genetics
  • !!Biophysics
  • !!Structural Biology
  • !!Biochemistry
  • !!Biotechnology
  • !!Computer Science Applications

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