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Related Concept Videos

RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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Statistical Methods for Analyzing Epidemiological Data01:25

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Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
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Statistical Methods to Analyze Parametric Data: ANOVA01:12

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Analysis of Variance, or ANOVA, is a powerful statistical technique used to analyze parametric data, primarily in research and experimental studies. It's designed to compare the means of two or more groups, assisting researchers in identifying any significant differences between these group means. There are two main types of ANOVA based on the complexity of the analysis: one-way and two-way.
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Statistical Methods to Analyze Parametric Data: Student t-Test and Goodness-of-Fit Test01:09

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In parametric statistics, two fundamental tests stand out for their utility and wide application: the Student's t-test and goodness-of-fit tests. These tests provide researchers with a robust method for drawing insights from data, testing hypotheses, and making informed decisions based on their findings.
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Eukaryotic RNA Polymerases00:58

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RNA Polymerase (RNAP) is conserved in all animals, with bacterial, archaeal, and eukaryotic RNAPs sharing significant sequence, structural, and functional similarities. Among the three eukaryotic RNAPs, RNA Polymerase II is most similar to bacterial RNAP in terms of both structural organization and folding topologies of the enzyme subunits. However, these similarities are not reflected in their mechanism of action.
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RNA Polymerase II Accessory Proteins02:36

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Proteins that regulate transcription can do so either via direct contact with RNA Polymerase or through indirect interactions facilitated by adaptors, mediators, histone-modifying proteins, and nucleosome remodelers. Direct interactions to activate transcription is seen in bacteria as well as in some eukaryotic genes. In these cases, upstream activation sequences are adjacent to the promoters, and the activator proteins interact directly with the transcriptional machinery. For example, in...
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Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
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GREIN: An Interactive Web Platform for Re-analyzing GEO RNA-seq Data.

Naim Al Mahi1, Mehdi Fazel Najafabadi1, Marcin Pilarczyk1

  • 1Division of Biostatistics and Bioinformatics, Department of Environmental Health, University of Cincinnati, 3223 Eden Avenue, Cincinnati, OH, 45220, USA.

Scientific Reports
|May 22, 2019
PubMed
Summary
This summary is machine-generated.

GREIN is a new web application that makes it easy to access and analyze RNA-seq data from the Gene Expression Omnibus (GEO). This tool helps researchers unlock the potential of publicly available RNA-sequencing experiments.

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Identification of Footprints of RNA:Protein Complexes via RNA Immunoprecipitation in Tandem Followed by Sequencing RIPiT-Seq
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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Vast amounts of RNA-sequencing (RNA-seq) data in public repositories like Gene Expression Omnibus (GEO) and Sequence Read Archive (SRA) remain underutilized.
  • Technical barriers hinder the effective reuse of these valuable genomic datasets for biomedical research.

Purpose of the Study:

  • To develop GREIN (GEO RNA-seq Experiments Interactive Navigator), a user-friendly web application.
  • To overcome technical challenges and facilitate the analysis and manipulation of GEO RNA-seq data.

Main Methods:

  • Developed a web application with a back-end computational pipeline for uniform RNA-seq data processing.
  • Integrated over 6,500 pre-processed RNA-seq datasets.
  • Implemented user-friendly front-end interfaces for data manipulation and analysis.

Main Results:

  • GREIN offers interactive visualization, data subsetting, and downloading capabilities.
  • Users can perform statistical power analyses and construct differential gene expression signatures.
  • Enables functional characterization and connectivity analysis with LINCS L1000 data.

Conclusions:

  • GREIN provides a unique, open-source resource for reusing GEO RNA-seq data.
  • The platform combines a large dataset with comprehensive analytical tools through an intuitive interface.
  • Facilitates deeper insights from publicly available RNA-seq experiments.