Bioinformatics Analyst, Cancer Research Unit

3 months ago


Saskatoon, Canada University of Saskatchewan Full time

Bioinformatics Analyst, Cancer Research Unit

Primary Purpose: The primary purpose of this position is to provide bioinformatics expertise, data analysis and support for health science researchers, particularly in the area of Cancer Research. This includes assistance with analysis of researcher-generated data ( Next-Generation sequencing data that may include: exome, whole genome, whole genome bisulfite, RNA-seq, ChIP-seq and other types of ‘omics data). In addition, the bioinformatics analyst will assist will analyses of data from the many large public databases to help researchers find, analyze, evaluate and report data relevant to the researcher’s questions. The successful candidate will have experience analyzing publicly available and newly generated genomics and transcriptomics data in a Linux/UNIX environment. Experience interpreting results in an oncological context is highly desirable.

Nature of Work: Reporting to the Cancer Cluster Lead, the Bioinformatics Analyst will support large scale sequencing and data analysis projects, as directed.

Typical Duties or Accountabilities: : Responsibilities of the Bioinformatics Analyst include, but are not limited to:

Processing of researcher generated sequencing data (, genomics, transcriptomics etc.) including data quality assessment, generating results using custom and established pipelines and workflows, and assisting with analysis and data interpretation Analyzing large public databases particularly those containing both ‘omics (genomics, gene expression, mutations etc.) and clinical data ( survival outcomes). Some examples include: cBioportal, TCGA, META500, CPTAC, GTEx, TARGET, gnomAD, GENIE, SEER Researching, implementing, and validating bioinformatic tools for specific project analyses Troubleshooting software and scripts Streamline and maintain NGS data analysis pipelines and manage storage of the datasets and results Organizing results into clear presentations, figures, or summaries.

Education: A minimum of bachelor’s in bioinformatics, computational biology, genomics or a related field with 2 years of experience. Preference would be given to Master’s or PhD degree holders with relevant experience

Experience: Previous experience performing processing and analyzing genomic and transcriptomic data is required

Skills:

Experience in analyzing and obtaining insights from high throughput sequencing data including RNA-seq, WGS and WES  Experience with Chip-Seq, ATAC-Seq, scRNA-Seq would be an asset
Experience integrating data from major public sources (, cBioportal, TCGA, META500, CPTAC, GTEx, TARGET, gnomAD, GENIE, SEER) to inform subsequent analyses is required
The ideal candidate will have experience using software tools and resources (, Ingenuity Pathway Analysis (IPA), Connectivity Map (CMAP, Broad Institute), KEGG Database and Pathways Analysis, Reactome Pathways Analysis, iPathwayGuide, DAVID, Innate DB, Bioconductor, XevaDB, ClinVar, PharmGKB, NIH LINCS, STRING, PPI Networks, UALCAN, KM plotter, CIBERSORT, DepMap) Experienced in using software tools and resources (, STAR, Bowtie2, GATK pipeline, DESEQ2, EdgeR, Ingenuity Pathway Analysis (IPA), Bioconductor, Conda)
Strong programming skills using multiple languages, including Python, Bash and R
Proficient in utilizing and programming within a High-Performance Computing (HPC) environment
Excellent communication skills. Ability to communicate results effectively to the researchers
Highly experienced in working independently and as part of a team and will also have a demonstrated track record of strong technical, analytical, organizational, time-management and communication skills.

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