By Mike Covington Date: Monday, 3 June 2013 11:45 Duration: 20 minutes Target audience: Any Language: English Tags: bioinformatics r_language sequence_analysis
The drop in the cost of DNA sequencing has resulted in the rapid generation of vast amounts of genome and transcriptome data. To efficiently analyze these data sets in novel ways, new bioinformatic tools must be built.
I will discuss a few tools I'm working on, including modules for identifying DNA/RNA sequence polymorphisms between related species, genotyping populations derived from these species, and identifying and assigning sequencing reads which ambiguously map to different parts of a transcriptome.
In addition to focusing on using Perl to analyze High-Throughput Sequencing data, I will also discuss how I use Statistics::R to interface with the statistical programming language, R.
I will discuss a few tools I'm working on, including modules for identifying DNA/RNA sequence polymorphisms between related species, genotyping populations derived from these species, and identifying and assigning sequencing reads which ambiguously map to different parts of a transcriptome.
In addition to focusing on using Perl to analyze High-Throughput Sequencing data, I will also discuss how I use Statistics::R to interface with the statistical programming language, R.
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