Commonly asked questions about CoGe.
What is CoGe?
CoGe is a online system for making the retrieval and comparison of genomic information and sequence quick and easy.
Why call it CoGe?
CoGe stands for Comparative Genomics.
Why make another comparative genomics system?
We found that existing comparative genomic systems were limited in their ability to accommodate genomic information and making it easily accessible for comparative analyses. We designed CoGe from the ground up to solve four major limitations:
- Store multiple versions of multiple genomes from multiple organism in a single platform
- Quickly find sequences of interest in genomes of interest (with associated information)
- Comparing multiple genomic regions using any algorithms
- Visualize the results of analyses in such a way as to make the identification of "interesting" patterns quick and easy.
All told, we wanted a comparative genomics system that would allow us to test our ideas and hypotheses as quick as possible so we could spend more time thinking about genomes and their evolution instead of trying to get and analyze genomic sequences.
Also, we realized that we wanted a system that allowed us to quickly develop new tools and add new genomic data as they become available. This means that when we load a new genome into CoGe, all the tools of CoGe are immediately available to analyze it. Likewise, if we develop a new tool to solve one particular problem with one set of genomes, it is immediately available to all the genomes in CoGe.
What is CoGe's sequence analysis workflow or pipeline?
While we designed CoGe to make it easy to find and comparing genomic sequences, there is no single, linear workflow through the system. Instead, there are central tools and access points that allow you to access the system to find sequences of interest, and "hub" points to take you from one part of the system to another. This allows for ideas to be generated while working CoGe, and be able to quickly branch out to investigate any number of interesting phenomena you find.
For example, you start with your favorite genome (mouse), do a whole genome comparison of it to human using SynMap, identify a region with an inversion, compare the breakpoints of that region in high-detail using GEvo, extract out the human sequence using SeqView, find all the protein coding regions using FeatView, use them to find homologs in other vertebrate genomes (e.g. chimp, mouse, and platypus) using CoGeBlast, validate putative syntenic regions using GEvo, find a particular gene extra interesting because of its copy-number variation in this syntenic region and get its sequence using FeatView once again, find putative intra- and inter-specific homologs of it using CoGeBlast, generate a fasta file of those putative homologs using FastaView, which you can align using CoGeAlign, and then use to build a phylogenetic tree using TreeView or export to more expansive phylogenetic tools-sets such as CIPRES. While waiting for your trees to be reconstructed, you decided to check out the codon and protein usage variation of the genes using FeatList, notice that there is some interesting variation in a couple of genes, check their over all GC content and wobble-position GC content FeatView, wonder if these have been horizontally transferred from the mitochondria, send those sequences to CoGeBlast to search mitochondrial genomes, find putative a homolog in several of those genomes, and then compare mitochondrial genomes to determine if there are inversions near those homologs using GEvo ...
In other words, there is no predefined end-point to an analysis.