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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- 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 variants compared to a reference genome. For higher eukaryotes uses tools such as GATK (Genome Analysis Toolkit) for SNP calling or MuTect2 for somatic mutations. Uses tools such as samtools mpileup or breseq for smaller genomes.
- 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.
- ChIP-Seq downstream analysis: Given a set of confident peak calls, this analysis may use a variety of tools to assess biological relevance. Examples include motif analysis, identification of possible regulatory targets, construction of regulatory networks, and differential binding analysis.
- 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: Compute clusters such as those available at the Texas Advanced Computing Center (TACC) offer massive resources for compute-intensive tasks on large data. However, optimizing pipelines to take advantage of the parallel architecture of a compute cluster often requires extra processing steps. We have experience with adapting existing pipelines and software to a massively parallel environment (such as the Trinity transcriptiome assembler and BLAST) and can work with researchers to adapt pipelines for HPC clusters.
- ddRAD analysis: Double digest RADseq offers a low-cost method for identifying polymorphisms in both model and non-model organisms. We offer ddRAD consulting services centered around the Stacks pipeline, with parameter optimization for the pipeline and parallelization on TACC compute clusters.
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