TY - JOUR
KW - Computational Biology
KW - Crops, Agricultural
KW - Databases, Genetic
KW - Genetic Variation
KW - Genomics
KW - Plants
KW - Software
KW - User-Computer Interface
KW - Web Browser
AU - Sushma Naithani
AU - Matthew Geniza
AU - Pankaj Jaiswal
AB - 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.
BT - Methods in molecular biology (Clifton, N.J.)
C1 - http://www.ncbi.nlm.nih.gov/pubmed/27987178?dopt=Abstract
DA - 2017
DO - 10.1007/978-1-4939-6658-5_17
J2 - Methods Mol. Biol.
LA - eng
N2 - 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.
PY - 2017
SP - 279
EP - 297
T2 - Methods in molecular biology (Clifton, N.J.)
TI - Variant Effect Prediction Analysis Using Resources Available at Gramene Database.
UR - https://dx.doi.org/10.1007/978-1-4939-6658-5_17
VL - 1533
SN - 1940-6029
ER -