Pejman Mohammadi

RecNW is a fast exact aligner for targeted sequencing that outperforms existing tools by using recurrence and unique read alignment.

The paper develops S-PrediXcan to compute gene expression associations from GWAS summary data and applies it to 44 GTEx tissues and 100+ phenotypes, finding tissue-specific effects and colocalized associations.

This paper introduces log allelic fold change (aFC) as a measure for quantifying cis-eQTL effect sizes, showing its consistency across datasets and independence from expression level and allele frequency.

The paper identifies response eQTLs that modify genetic regulation during immune activation and shows their enrichment in autoimmune disease GWAS signals.

This paper introduces phASER, a method for phasing variants from RNA-seq data, improving accuracy for rare and de novo variants and enabling haplotypic expression analysis.

The paper estimates that 10.8% of human genes are haploinsufficient based on truncating variants in 11,546 individuals.

This paper analyzes allelic expression read count data, identifies technical errors, and introduces software for high-throughput AE analysis to improve data quality.

The paper develops a Bayesian classification scheme to rank the pathogenicity of stop-gain and frameshift variants in innate immunity genes using sequence-based features and validates it against known disease variants.