The Bioinformatics group offers support to researchers within UT and outside to assist with management and analysis of large scale data. We use "best practices" highly cited open source tools as well as tools developed within our group for our data analysis.
By having one of our Consultants perform data analysis, you can be assured that:
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Full service pipelines available
- Benchmarking of tools/pipelines: New bioinformatics tools are introduced everyday and a thorough comparison is required to select the most appropriate tool. Evaluation of bioinformatics tools for accuracy and performance will be performed using simulated and/or real data.
- DNA-Seq variant calling pipeline: Identification and annotation of SNPs and/or somatic mutations compared to reference genome. 10 hour minimum ($730 internal, $930 external) per project.
- RNA-Seq analysis pipeline: This pipeline uses an annotated genome/transcriptome to identify differential expressed genes/transcripts. 15 hour minimum ($1095 internal, $1395 external) per project.
- RNA-Seq for non-model organisms: For non-model organisms, a representative transcriptome will be assembled using tools like Trinity. This assembly will be evaluated for completeness and annotated using homology search tools. By mapping to this annotated transcriptome, differentially expressed genes/transcripts will be identified.
- Network/Co-expression analysis: Tools like WGCNA (weighted co-expression network analysis) will be used to identify patterns of correlation in gene/transcript expression in order to identify co-expressed/potentially co-regulated genes.
- ChIP-Seq peak calling pipeline: This pipeline identifies regions of significant protein binding ("peaks") based on an annotated genome. 10 hour minimum ($730 internal, $930 external) per project.
- Transcriptome assembly: Assembly of RNA-seq short reads into a transcriptome. 12 hour minimum ($876 internal, $1116 external) per project.
- Genome assembly: Assembly of genomes using short read data will be performed using tools like Velvet , Allpaths (for specific library types) and SPAdes (for bacterial genomes). If long read technology like PacBio reads are available, they can also be incorporated to improve the genome assembly. The assemblies will be evaluated for completeness and will be annotated using tools like MAKER.
- Data visualization:
- Promoter analysis:
- Statistical analysis/Biostatistics problems:
- 16s Sequencing using QIIME:
- Application development/Optimization of pipelines to run on HPC environments:
- ddRAD analysis:
Rates
Internal customers (payment from a UT Austin account): $73/hour
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