Forum:Kai Wang of Annovar and PennCNV uses this
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9.5 years ago

Dr. Kai Wang is an Assistant Professor in the Department of Psychiatry & Behavioral Sciences of the University of Southern California. He graduated in 2000 from Peking University then received a Ph.D. in 2005 from the University of Washington. Currently Dr. Wang directs and supervises a genomics lab at USC where his group develops an impressive array of genomics software among them

  • Annovar a command line software for functional annotation of genetic variants from high-throughput sequencing data and,
  • PennCNV a software for detecting copy number variations (CNVs) from SNP arrays.

Tools developed by Dr. Wang have been cited in thousands of research papers and constitute the foundation that hundreds of research groups rely on for their discoveries.

Biobase offers commercial level support for Annovar.


What hardware do you use?

Currently I use a Macbook (with Windows 7) for daily email, web browsing and writing, and use a custom-built computing cluster (Linux) for heavy computation and analysis.

What is your text editor?

I use UltraEdit for coding, and vim for simple text editing.

What software do you use for your work?

For my research, I use many bioinformatics tools, including those developed for,

  • alignment (for example BWA/Tophat/STAR)
  • variant calling (for example, FreeBayes/VarScan/GATK),
  • variant annotation (for example, ANNOVAR/UCSC Genome Browser),
  • helper tools (BLAT/liftOver/SAMtools),
  • differential expression (for example, DESeq/Cuffdiff),
  • data visualization (for example, IGV/Circos)

and many others.

What do you use to create plots and charts?

I typically just use Excel and Powerpoint. For publication quality work, R and Illustrator are used.

What do you consider the best language to do bioinformatics with?

For historical reasons I am only good at C and Perl, and I use Perl most of the time. My lab members use a variety of languages such as Java, Ruby, Python, R and PHP/JS, but I think as long as it can accomplish a task and allows easy maintenance, the choice of language is not so critical.

What bioinformatics tools/software do not get enough recognition?

A few tools can perhaps get more recognition/attention:


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