Chapter title |
Variant Effect Prediction Analysis Using Resources Available at Gramene Database.
|
---|---|
Chapter number | 17 |
Book title |
Plant Genomics Databases
|
Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-6658-5_17 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6656-1, 978-1-4939-6658-5
|
Authors |
Sushma Naithani, Matthew Geniza, Pankaj Jaiswal |
Editors |
Aalt D.J van Dijk |
Abstract |
The goal of Gramene database ( www.gramene.org ) is to empower the plant research community in conducting comparative genomics studies across model plants and crops by employing a phylogenetic framework and orthology-based projections. Gramene database (release #49) provides resources for comparative plant genomics including well-annotated plant genomes (39 complete reference genomes and six partial genomes), genetic or structural variation data for 14 plant species, pathways for 58 plant species, and gene expression data for 14 species including Arabidopsis, rice, maize, soybean, wheat, etc. (fetched from EBI-EMBL Gene Expression Atlas database). Gramene also facilitates visualization and analysis of user-defined data in the context of species-specific Genome Browsers or pathways. This chapter describes basic navigation for Gramene users and illustrates how they can use the genome section to analyze the gene expression and nucleotide variation data generated in their labs. This includes (1) upload and display of genomic data onto a Genome Browser track, (2) analysis of variation data using online Variant Effect Predictor (VEP) tool for smaller data sets, and (3) the use of the stand-alone Perl scripts and command line protocols for variant effect prediction on larger data sets. |
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Unknown | 1 | 100% |
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Members of the public | 1 | 100% |
Mendeley readers
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Unknown | 9 | 100% |
Demographic breakdown
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Student > Ph. D. Student | 2 | 22% |
Professor > Associate Professor | 1 | 11% |
Researcher | 1 | 11% |
Student > Master | 1 | 11% |
Unknown | 4 | 44% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 2 | 22% |
Mathematics | 1 | 11% |
Psychology | 1 | 11% |
Engineering | 1 | 11% |
Unknown | 4 | 44% |