Choosing the right normalization method depends on the specific objectives of your RNA-Seq analysis. TPM’s proportionality and robustness make it the preferred choice for most applications, while CPM serves well for differential expression...
http://shinyheatmap.com/ - Background: Transcriptomics, metabolomics, metagenomics, and other various next-generation sequencing (-omics) fields are known for their production of large datasets. Visualizing such big data has posed technical challenges in biology, both in...
chagall.med.cornell.edu - RNAseq can be roughly divided into two "types":
Reference genome-based - an assembled genome exists for a species for which an RNAseq experiment is performed. It allows reads to be aligned against the reference genome and significantly improves...
Live Webinar on Streamlining large scale NGS data analysis using the Strand NGS Pipeline Manager on 24 Feb 2016
Abstract: Strand NGS includes comprehensive workflows for DNA-Seq, RNA-Seq, Small RNA-Seq, ChIP-Seq, MeDIP-Seq, and Methyl-Seq analysis....
We are seeking one motivated scientist to analyze genomics and transcriptomics data of a large collection of neuroblastoma tumors. The successful candidate will be part of a team of researchers with extensive expertise in genome cancer study. He/she...
http://bit.ly/e8QGzY Human genome mapping is now enabling a breakthrough in medical innovation -- personalized medicine. What does this mean for patients? We can now identify predispositions to disease, predict how we metabolize drugs, and figure...
May 21, 2014 - Current Topics in Genome Analysis 2014
A lecture series covering contemporary areas in genomics and bioinformatics. More: http://www.genome.gov/COURSE2014
Our research group is primarily focused on the analysis of whole genome sequence data to identify genetic variation (primarily structural variation) and examine their potential functional impact in disease phenotypes. We are particularly interested...
