Bioinformatics and High Performance Computing (HPC) Server facility
Augusta University
Contact: Sam Chang, Ph.D., Director Georgia Cancer Center Bioinformatics Shared Resource
Phone: 706-446-5528
The GCC Bioinformatics Shared Resource provides expertise in integrative computational-based analysis solutions to basic, clinical, and translational research applications. Bioinformatics support ranges in scope from simple consultations to more in-depth collaborations. We require the participation of the investigator during the course of our data analysis because we believe that input into the biological parameters is critical to success of the analyses.
High-Performance Computing Server (HPC)
Campus users have access to several advanced computing servers owned by the Georgia Cancer Center, including a High-Performance Computing Server (HPC) that has 544 total compute cores and an aggregated memory of 2.9TB. The system is composed of 15 PowerEdge R430 1U systems (128 GB RAM each node), 1 PowerEdge R830 (high memory 1024 GB RAM node), and a high-speed 40GbE interconnect for intraserver communication. The HPC also houses 652 TB RAW storage capacity known as Qumulo, allowing the functionalities of effective management and maintenance as well as highly efficient analysis of large data sets, and is committed to the Bioinformatics Shared Resource. Training or knowledge of Linux is required to use the HPC server.
Services
Quality Assessment
- Assess the quality of sequencing for various kinds of metrics
Differential Methylation
- Perform statistical tests
- Generate a table for methylation change, p-values, and q-values
- Generate figures for differential methylation analysis
- Annotate differentially methylated regions
- Prepare tracks for the IGV genome browser
Read Mapping
- Align sequence reads to reference sequences
- Summarize mapping results
- Generate BAM, and BigWig files for the IGV genome browser
Enrichment Identification
- Identify enriched regions (peaks) using statistical models
- Generate a table for enriched regions
- Generate figures for quality control of peak calling
- Generate tag density plots for genomic features
- Prepare tracks for the IGV genome browser
Sequence Variants
- Identify sequence variants
- Generate VCF files
- Annotate sequence variants
- Compare to known databases
- Select high quality of variants by user’s criteria
- Prepare tracks for the IGV genome browser
Differential Enrichment
- Perform statistical tests
- Generate a table for fold change, p-values, and q-values
- Generate figures for differential enrichment analysis
- Annotate differentially enriched regions
- Prepare tracks for the UCSC genome browser
Structure Variants
- Identify structure variants
- Generate VCF files
- Annotate structure variants
- Compare to known databases
- Select high quality of variants by user’s criteria
- Prepare tracks for the IGV genome browser
Sequence Motif
- Discover sequence motifs from peaks
- Search peaks for sequence motifs
- Compare to known databases
- Generate binding logos for sequence motifs
Expression Profile
- Generate a table for read counts and FPKMs
- Generate figures for quality control analysis
- Assess the variation between samples and replicates
- Detect outliers
Gene Set Enrichment Analysis
- Prepare input files for GSEA
- Run GSEA
- Summarize the results
Differential Expression
- Perform statistical tests
- Generate a table for fold change, p-values, and q-values
- Generate figures for differential expression analysis
Functional Annotation
- Prepare input files
- Compare gene sets with GO terms and pathways
Alternative Splicing
- Measure alternative splicing in each sample
- Compare samples or groups for splicing changes
- Summarize alternative splicing and splicing changes
- Generate figures for alternative splicing and splicing change analysis
De Novo Genome Assembly
- Assemble sequence reads
- Assess assembly statistics
- Validate an assembly
- Run BLAST to a nucleotide database
- Compare to the closest public genomes
- Ab initio gene prediction
Gene Fusion
- Generate a table and figure for gene fusion
De Novo Transcriptome Assembly
- Assemble sequence reads
- Assess assembly statistics
- Run BLAST to a protein database
- Compare to the closest public transcriptomes
- Find orthologs and paralogs
Methylation Profile
- Generate a table for beta values
- Generate figures for quality control
- Assesses the variation between samples and replicates
- Detect outliers
- Prepare tracks for the IGV genome browser
NCBI Deposit
- Generate necessary files in appropriate formats
- Help to fill the form in meta files
- Upload files onto NCBI database
More about this core facility at Augusta University's website »
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