Viral / Molecular Core High Density Sequencing Support
High density sequencing is an emerging technology with the capacity to generate millions of sequences, with up to a billion bases of sequence in a single run. This approach is ideal for characterizing complex populations such as HIV and SIV, HBV/HCV, and sites of retroviral DNA integration.
The Viral/Molecular Core is now offering Illumina sequencing as a service. In each case, amplicons will be generated from samples of interest, then sample sequences determined. Sequences are subject to stringent quality control algorithim and provided to users in fasta format. Bioinformatic analysis is available on a fee-for-service basis. The core also provides advice on experimental design, sequence work up, statistical analysis, and long term data storage.
Several services are offered.
- Initial consultation on experimental design (free of charge)
- Deep sequencing of viral genomes
- Sequencing of sites of retroviral DNA integration
- Programmer time for data analysis
The Core provides support for each of these areas through the expertise of Dr. Frederic Bushman (Core Co-Director). Advanced bioanalytic support and analysis is offered collaboratively through the Biostatistics and Data Management Core (Core G) by Dr. Hongzhe Li (Core G Co-Investigator).
For further information on utilizing V/M Core support for high density sequencing, contact Aubrey Bailey.
Order High Density Sequencing services through the Path BioResource at Penn. Instructions for the Path BioResource can be found here on the CFAR website or on the Path BioResource site itself.
Core Service Contact:
Viral and Molecular Core
The V/M Core can provide free collaborative biostatistical services including proposal development and study design, framing hypotheses, sample size calculation, selection of statistical methods, grant applications, interpretive analyses and manuscript writing.
If a grant results from this collaboration with effort budgeted for a student/analyst, the V/M Core can then continue to provide collaboration on data analysis.