Summary

A Bioinformatics Analyst I position is available in Dr. Graham Erwin's laboratory in the Department of Molecular and Human Genetics at Baylor College of Medicine. Our lab investigates the functional role of repetitive DNA sequences in human health and disease, with a focus on somatic variation between human tissues. We are seeking a talented and motivated analyst to join our bioinformatics team in discovering and analyzing genomic variation in normal human and disease populations, with an emphasis on cancer genomics. The successful candidate will utilize computational tools and techniques to process next-generation sequencing data, identify structural variants, and contribute to ongoing research projects exploring the role of repeat expansions in cancer and other complex diseases.

Job Duties

• Runs and validates bioinformatic pipelines for detecting genomic variation, particularly structural variants such as tandem repeat expansions, from short-read and long-read whole-genome sequencing data.
• Processes raw sequencing data using established workflows to identify various types of genomic variants, including small variants (SNVs and INDELs) and larger structural variants with a focus on repeat expansions.
• Applies read depth normalization techniques and other filtering strategies to account for copy number variations and other confounding factors in cancer genomics data.
• Performs comparative analyses of genetic variation between different human tissue types, tumor and normal samples, or across multiple cancer types.
• Uses specialized tools such as ExpansionHunter, ExpansionHunter Denovo, TRGT, TRVZ, and other variant detection software to identify and characterize repeat expansions.
• Assists in the interpretation of variant data, especially in the context of regulatory elements and gene function.

Minimum Qualifications

• Bachelor's degree in Genetics, Biology, Bioinformatics, Biostatistics, Computational Biology, Computer Science, or a related field.
• No experience required.

Preferred Qualifications

• Master’s degree in a related field.

• Programming skills in languages such as Python, R, or Bash scripting.

• Experience with next-generation sequencing data analysis and large-scale genomic datasets.

• Familiarity with structural variant detection and analysis, particularly for tandem repeat expansions, including both short read and long read DNA sequencing.

• Expertise of our research area (tandem repeats, structural variation, long read sequencing) is a priority.