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  • variant annotation

    Hi,
    Most of the tools related to variant annotations seem to be related to humans. I work on a plant species where we only have the draft genome and not annotated yet. I have done an rna-seq experiment and I have found several snps using samtools. I got a gtf file by aligning reads against the genome sequence with bowtie and tophat. The gtf file only has transcirpt information and no orf or CDS information. Does any one have a script which takes the positions of the snps, annotations from a gtf file and the genome sequence in fasta format and predict if the snps are synonymous or non-synonymous?

  • #2
    Hi,
    I am too am facing this problem.
    I am working on a bacterial genome. I have the Genome sequence, the gene annotations gff file and and list of variations (not annotated).

    How do I annotate the variants using the gff file and the genome sequence file, to map the variants to genes.

    Any ideas how to go about?
    tx,
    Durga

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    • #3
      Hi Durga,
      I use a script in 'popoolation' (http://code.google.com/p/popoolation/) package to annotate the variants. You need to supply a pileup file and a gtf file with CDS to annotate the variants.

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      • #4
        You could use SNPdat (http://code.google.com/p/snpdat). Its available from BMC bioinformatics
        Background Single nucleotide polymorphisms (SNPs) are the most abundant genetic variant found in vertebrates and invertebrates. SNP discovery has become a highly automated, robust and relatively inexpensive process allowing the identification of many thousands of mutations for model and non-model organisms. Annotating large numbers of SNPs can be a difficult and complex process. Many tools available are optimised for use with organisms densely sampled for SNPs, such as humans. There are currently few tools available that are species non-specific or support non-model organism data. Results Here we present SNPdat, a high throughput analysis tool that can provide a comprehensive annotation of both novel and known SNPs for any organism with a draft sequence and annotation. Using a dataset of 4,566 SNPs identified in cattle using high-throughput DNA sequencing we demonstrate the annotations performed and the statistics that can be generated by SNPdat. Conclusions SNPdat provides users with a simple tool for annotation of genomes that are either not supported by other tools or have a small number of annotated SNPs available. SNPdat can also be used to analyse datasets from organisms which are densely sampled for SNPs. As a command line tool it can easily be incorporated into existing SNP discovery pipelines and fills a niche for analyses involving non-model organisms that are not supported by many available SNP annotation tools. SNPdat will be of great interest to scientists involved in SNP discovery and analysis projects, particularly those with limited bioinformatics experience.

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