The Bioinformatics Core Laboratory provides computational expertise and resources for the design and analyses of high-throughput assays and for comparisons and integration of Texas Children's Hospital data with data derived from external knowledge bases. The Bioinformatics Core Laboratory will provide state-of-the-art, secure, regulatory-compliant and customized solutions to address clinical and research needs at Texas Children's Hospital.
The Bioinformatics Core Laboratory occupies a 600 sq. ft. office in the 12th floor of the Texas Children's Hospital Feigin Center, including six workstations and a projector. It employs three bioinformaticians with degrees (2 PhDs and one MS) in Computer Science, Mathematics, Physics, Genetics, and Biomedical Informatics.
Faculty and staff within the core have contributed experience in high-throughput experiment design and in various methods for the analysis of molecular and clinical profiles. Faculty and staff within the core have also contributed to over 50 published manuscripts including publications in Cell, Cancer Cell, Genome Research, Nature Communications, and Science Cell Signaling.
The laboratory personnel has also advised on predictive biomarker discovery for both research and clinical applications.
Computing. 600-core cluster with Infiniband. QDR QSFP interconnect all nodes Storage/head node with 40 TB RAID for working storage, 32 TB of shared Lustre-style distributed scratch space, 16 cores, 2.6/3.3ghz (2x E5-2670, Sandy Bridge)
Power estimates and study design including platform and data volume choice
Quality control, normalization, testing for systematic technical errors
DNA sequencing analysis, including variant calling
RNA sequencing analysis, including expression and differential expression
Analyzing ChIP and epigenetics data
Gene-set enrichment and pathway analyses
Integrative analysis across omics, including: RNA, DNA data, functional data
Statistical cross validation with published data sets
Obtaining, storing and reanalyzing public data
Integration of external data sets with analyzed omics data to identify common and unique features
Integrating external case-control studies, including population stratification
Applying lessons learned from large-scale molecular data, such as TARGET and TCGA data, to locally-produced data and vice versa
Domain-specific analyses, including genetic tests and rare variant grouping and burden tests
Prediction of functional variants using molecular profiling of multiple tumors
Prediction of functional variants using integrative analysis of multiple assays and clinical data
Inference of clonal composition of tumors based on their molecular profiles
Prediction of off-target effects in CRISPR assays
Presentation of results
Protein expression analysis - Identify differentially expressed genes
Request for Services
To request services, please complete this request form. Appointments are available Monday-Friday from 9:00 a.m. – 5:00 p.m. Earlier or later appointments may be available with the approval of the lab director.