Bioinformatician / August, 2022 — Present

Developing and maintaining NGS analysis pipeline by the addition of annotation of SNVs. Also, developing a structure variation calling pipeline by the addition of long read technology. Proficient with Python, R, and bash scripting.

Research Scientist / April, 2020 — August, 2022

Developed a python custom pipeline for SNP annotation. Briefly, gnomAD sequencing data is appended with SeattleSeq Annotation results among 3 gene panels. There are also filtering by transcript steps and options to filter out excessive gnomAD data. Investigated structural variation in the VWF gene, mediated by VWFP1. Developed 2 bash script pipelines using Hydra and Lumpy in this effort. Also became familiar with Smoove, Cn.mops and CNVpytor. In addition, I wrote python scripts to count reads (depth) by kmers that distinguish between VWF and VWFP1 sequence. Alignment was performed with BLAT. Completed variant calling pipeline in bash from raw fastq data to vcf data. The primary applications are BWA, GATK, Samtools, and Picard. Use of many databases such as gnomAD, UCSC Genome Browser, Ensemble, and NCBI. Python annotation pipeline and bash scripts available upon request.

Genomics Researcher / June, 2019 — April, 2020

Alignments of amplicons (generated from RADseq) to reference genome sequence in several species of salmonids. Comparisons of BWA and Bowtie2. Documentation of multiple aligned amplicons and determination of SNP coordinates in genome from fastq sequences. Use of SnpEff to annotate above SNP variants. Extensive use of Samtools, Bcftools, and GATK for variant calling. Run IGB to visualize bam files. Routinely program and call commands in the Linux environment. Knowledgeable of Ensembl genome browser variant effect predictor. Maintain and edit GTseq pipeline (perl scripts). Use of mummer to align large DNA sequences.

Research Scientist 4 / July, 2014 — May, 2019

Alignment of fastq files generated on a MiSeq using BWA. Generate read count and ratio distributions on a per gene basis. Calculate probabilities from distributions and create linear regression of control/treatment data frames in R. Wrote python scripts to facilitate large scale data analysis. RNAseq analysis (DESeq2 and cufflinks) of count data to determine differential expression between different treatments. Good understanding of tophat, bowtie, Fisher’s exact test, Wald statistic, normalization methods, and variance modeling using the negative binomial distribution.

Research Scientist 3 / June, 1994 — July, 2014

Analysis of next generation sequence (whole and exome) data sets by fastq alignments, QC analysis, and gene annotating with SeattleSeq Annotation. Experience with multiple quality checks of DNA sequence data such as sequencing depth, length distributions, base quality scores, percent reads mapped, allele distributions per cycle, and duplication distributions. Also, used variant calling software GATK to identify SNPs (biomarkers for cardiomyopathy, prostate cancer) and gained a strong understanding of variant call formats (VCF) and Bayesian statistics to call genotypes. Experience with the following software and packages in R - ExomeDepth, Varscan, and Mutect.