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Pak Chung Sham

Publications and source records attributed to Pak Chung Sham.

3 recordsLinked to original sources

Endogenous fine-mapping and prioritization of functional regulatory elements in complex genetic loci.

Most genetic loci linked to polygenic traits are in non-coding regions, with complex regulation and linkage disequilibrium (LD), complicating causal variant and gene prioritization. We used multiplexed single-cell CRISPR interference and activation perturbations to investigate cis-regulatory element (CRE) and gene expression relationships within tight LD in the endogenous chromatin context. We demonstrated the prevalence of multiple causality in perfect LD (pLD) for independent expression quantitative trait loci (eQTLs) and uncovered fine-grained genetic effects on gene expression within pLD, which are difficult to decipher using traditional eQTL fine-mapping or existing computational methods. We found that over one-third of the causal CREs lack classical epigenetic markers prior to perturbation, and we functionally validated one of these hidden regulatory mechanisms. Leveraging Multiome single-cell epigenetic and sequence perturbations, we highlighted the regulatory plasticity of the human genome. Our study will guide the exploration of missing causal mechanisms underlying molecular trait regulation and disease development.

Humans↗

Generic number systems and haplotype analysis.

Three simple and elegant algorithms involving binary and mixed-radix numbers are presented as C subroutines and applied to gene-counting procedure. The first, a multikey radix-sorting subroutine, is used to tally individuals with similar genetic marker information. The second, a subroutine for N-ary number addition, is used to enumerate all possible phases of a heterozygote. The third, a mixed-radix number subroutine, is used to generate all haplotypes and indexing single array of haplotype frequencies. Examples exposing these algorithms are also given. The sorting algorithm entails broad application while the N-ary and mixed-radix number algorithms are very efficient for generic looping. Implementation of gene-counting using these algorithms avoids use of multilocus genotype identifier and improves its portability to other analysis.

Algorithms↗