pyPAGE: A framework for Addressing biases in gene-set enrichment analysis-A case study on Alzheimer's disease.

Inferring the driving regulatory programs from comparative analysis of gene expression data is a cornerstone of systems biology. Many computational frameworks were developed to address this problem, including our iPAGE (information-theoretic Pathway Analysis of Gene Expression) toolset that uses information theory to detect non-random patterns of expression associated with given pathways or regulons. Our recent observations, however, indicate that existing approaches are susceptible to the technical biases that are inherent to most real world annotations. To address this, we have extended our information-theoretic framework to account for specific biases and artifacts in biological networks using the concept of conditional information. To showcase pyPAGE, we performed a comprehensive analysis of regulatory perturbations that underlie the molecular etiology of Alzheimer's disease (AD). pyPAGE successfully recapitulated several known AD-associated gene expression programs. We also discovered several additional regulons whose differential activity is significantly associated with AD. We further explored how these regulators relate to pathological processes in AD through cell-type specific analysis of single cell and spatial gene expression datasets. Our findings showcase the utility of pyPAGE as a precise and reliable biomarker discovery in complex diseases such as Alzheimer's disease.

Sensitive, Highly Multiplexed Sequencing of Microhaplotypes From the Plasmodium falciparum Heterozygome.

BACKGROUND: Targeted next-generation sequencing offers the potential for consistent, deep coverage of information-rich genomic regions to characterize polyclonal Plasmodium falciparum infections. However, methods to identify and sequence these genomic regions are currently limited. METHODS: A bioinformatic pipeline and multiplex methods were developed to identify and simultaneously sequence 100 targets and applied to dried blood spot (DBS) controls and field isolates from Mozambique. For comparison, whole-genome sequencing data were generated for the same controls. RESULTS: Using publicly available genomes, 4465 high-diversity genomic regions suited for targeted sequencing were identified, representing the P. falciparum heterozygome. For this study, 93 microhaplotypes with high diversity (median expected heterozygosity = 0.7) were selected along with 7 drug resistance loci. The sequencing method achieved very high coverage (median 99%), specificity (99.8%), and sensitivity (90% for haplotypes with 5% within sample frequency in dried blood spots with 100 parasites/µL). In silico analyses revealed that microhaplotypes provided much higher resolution to discriminate related from unrelated polyclonal infections than biallelic single-nucleotide polymorphism barcodes. CONCLUSIONS: The bioinformatic and laboratory methods outlined here provide a flexible tool for efficient, low-cost, high-throughput interrogation of the P. falciparum genome, and can be tailored to simultaneously address multiple questions of interest in various epidemiological settings.

Optimization of whole-genome sequencing of Plasmodium falciparum from low-density dried blood spot samples.

BACKGROUND: Whole-genome sequencing (WGS) is becoming increasingly useful to study the biology, epidemiology, and ecology of malaria parasites. Despite ease of sampling, DNA extracted from dried blood spots (DBS) has a high ratio of human DNA compared to parasite DNA, which poses a challenge for downstream genetic analyses. The effects of multiple methods for DNA extraction, digestion of methylated DNA, and amplification were evaluated on the quality and fidelity of WGS data recovered from DBS. METHODS: Low parasite density mock DBS samples were created, extracted either with Tween-Chelex or QIAamp, treated with or without McrBC, and amplified with one of three different amplification techniques (two sWGA primer sets and one rWGA). Extraction conditions were evaluated on performance of sequencing depth, percentiles of coverage, and expected SNP concordance. RESULTS: At 100 parasites/µL, Chelex-Tween-McrBC samples had higher coverage (5 × depth = 93% genome) than QIAamp extracted samples (5 × depth = 76% genome). The two evaluated sWGA primer sets showed minor differences in overall genome coverage and SNP concordance, with a newly proposed combination of 20 primers showing a modest improvement in coverage over those previously published. CONCLUSIONS: Overall, Tween-Chelex extracted samples that were treated with McrBC digestion and are amplified using 6A10AD sWGA conditions had minimal dropout rate, higher percentages of coverage at higher depth, and more accurate SNP concordance than QiaAMP extracted samples. These findings extend the results of previously reported methods, making whole genome sequencing accessible to a larger number of low density samples that are commonly encountered in cross-sectional surveys.