Bioinformatics and High Performance Computing (HPC) Server facility

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 NovoTranscriptome 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