Biology subjects

Chaturvedi, N.

Publications and source records attributed to Chaturvedi, N..

At least 19 recordsLinked to original sources

bioRxiv2025

Accurate Variant Classification in Tumour-Only Genomic Data Using Interpretable Tabular Models

Recent work has shown that machine learning can provide a reliable tool to classify somatic and rare germline variants in cancer studies where matched-normal samples are not available. Here, we present a workflow that combines an opensource pipeline with three machine-learning models, XGBoost, LightGBM, and TabNet, trained on eight types of features. Our approach substantially enhances the accuracy across all tested models providing accurate results irrespective of sample ancestry and tumour type. We build a parsimonious model and demonstrate that training on low-coverage data retains high accuracy when applied to high-coverage data and vice versa. In contrast to previous findings, our results indicate that XGBoost slightly outperforms LightGBM, achieving high classification accuracy even in the absence of copy-number information and allowing for the ancestry-unbiased calculation of the tumour mutational burden for different types of cancer.

bioinformatics↗

bioRxiv2025

Multi-cohort, multi-sequence harmonisation for cerebrovascular brain age

IntroductionHigher brain-predicted age gaps (BAG), based on anatomical brain scans, have been associated with cognitive decline among elderly participants. Adding a cerebrovascular component, in the form of arterial spin labelling (ASL) perfusion MRI, can improve the BAG predictions and potentially increase sensitivity to cardiovascular health, a contributor to brain ageing and cognitive decline. ASL acquisition differences are likely to influence brain age estimations, and data harmonisation becomes indispensable for multi-cohort brain age studies including ASL. In this multi-cohort, multi-sequence study, we investigate harmonisation methods to improve the generalisability of cerebrovascular brain age. MethodsA multi-study dataset of 2608 participants was used, comprising structural T1-weighted (T1w), FLAIR, and ASL 3T MRI data. The single scanner training dataset consisted of 806 healthy participants, age 50{+/-}17, 18-95 years. The testing datasets comprised four cohorts (n=1802, age 67{+/-}8, 37-90 years). Image features included grey and white matter (GM/WM) volumes (T1w), WM hyperintensity volumes and counts (FLAIR), and ASL cerebral blood flow (CBF) and its spatial coefficient of variation (sCoV). Feature harmonisation was performed using NeuroComBat, CovBat, NeuroHarmonize, OPNested ComBat, AutoComBat, and RELIEF. ASL-only and T1w+FLAIR+ASL brain age models were trained using ExtraTrees. Model performance was assessed through the mean absolute error (MAE) and mean BAG. ResultsASL feature differences between cohorts decreased after harmonisation for all methods (p<0.05), mostly for RELIEF. Negative associations between age and GM CBF (b=-0.37, R2=0.13, unharmonised) increased after harmonisation for all methods (b<-0.42, R2>0.12) but weakened for RELIEF (b=-0.28, R2=0.14). In the ASL-only model, MAE improved for all harmonisation methods from 11.1{+/-}7.5 years to less than 8.8{+/-}6.2 years (p<0.001), while BAGs changed from 0.6{+/-}13.4 years to less than -1.03{+/-}7.92 years (p<0.001). For T1w+FLAIR+ASL, MAE (5.9{+/-}4.6 years, unharmonised) increased for all harmonisation methods non-significantly to above 6.0{+/-}4.9 years (p>0.42) and significantly for RELIEF (6.4{+/-}5.2 years, p=0.02), while BAGs non-significantly differed from -1.6{+/-}7.3 years to between -1.3{+/-}4.7 and -2.0{+/-}8.0 years (p>0.82). In general, the ASL-specific parameter harmonisation method AutoComBat performed nominally best. DiscussionHarmonisation of ASL features improves feature consistency between studies and also improves brain age estimations when only ASL features are used. ASL-specific parameter harmonisation methods perform nominally better than basic mean and scale adjustment or latent-factor approaches, suggesting that ASL acquisition parameters should be considered when harmonising ASL data. Although multi-modal brain age estimations were improved less by ASL-only harmonisation, possibly due to weaker associations between age and ASL features compared to T1w features feature importance, studies investigating pathological ASL-feature distributions might still benefit from harmonisation. These findings advocate for ASL-parameter specific harmonisation to explore associations between cardiovascular risk factors, brain ageing, and cognitive decline using multi-cohort ASL and cerebrovascular brain age studies.

neuroscience↗

bioRxiv2024

Convergent cellular adaptation to a quiescence-like state in response to freeze-thaw stress

Extreme stress, such as freeze-thaw, poses a severe challenge to many organisms, but the mechanisms underlying their adaptation to survive such stress remain elusive. Here, we show that Saccharomyces cerevisiae can rapidly evolve freeze-thaw tolerance through a physiological state transition, with survival increasing nearly two orders of magnitude from {approx}2% to {approx}70% in about 25 cycles of stress exposure. Evolved yeast cells exhibit a quiescence-like state, characterized by altered cellular physiology: increased intracellular trehalose accumulation, reduced membrane damage, cytoplasmic stiffening and an exit from a proliferative cycle. This mechano-chemically reinforced survival strategy emerges across independent evolutionary lines despite distinct genetic backgrounds, suggesting a convergent mechanism of adaptation. By integrating experimental evolution, biophysical measurements, genomic analysis, and a quantitative model that captures the adaptation dynamics, we reveal that stress tolerance can arise via a potentially generalizable, physiologically mediated adaptation strategy. These findings provide new insights into microbial survival under extreme conditions and suggest broader implications for cellular stress responses beyond yeast.

evolutionary biology↗

bioRxiv2023

EHD1-dependent traffic of IGF-1 receptor to the cell surface is essential for Ewing sarcoma tumorigenesis and metastasis

Overexpression of EPS15 Homology Domain containing 1 (EHD1) has been linked to tumorigenesis but whether its core function as a regulator of intracellular traffic of cell surface receptors plays a role in oncogenesis remains unknown. We establish that EHD1 is overexpressed in Ewing sarcoma (EWS), with high EHD mRNA expression specifying shorter patient survival. ShRNA and CRISPR-knockout with mouse Ehd1 rescue established a requirement of EHD1 for tumorigenesis and metastasis. RTK antibody arrays identified the IGF-1R as a target of EHD1 regulation in EWS. Mechanistically, we demonstrate a requirement of EHD1 for endocytic recycling and Golgi to plasma membrane traffic of IGF-1R to maintain its surface expression and downstream signaling. Conversely, EHD1 overexpression-dependent exaggerated oncogenic traits require IGF-1R expression and kinase activity. Our findings define the RTK traffic regulation as a proximal mechanism of EHD1 overexpression-dependent oncogenesis that impinges on IGF-1R in EWS, supporting the potential of IGF-1R and EHD1 co-targeting.

cancer biology↗

bioRxiv2020

Validation of lipid-related therapeutic targets for coronary heart disease prevention using human genetics

Drug target Mendelian randomization (MR) studies use DNA sequence variants in or near a gene encoding a drug target, that alter its expression or function, as a tool to anticipate the effect of drug action on the same target. Here, we applied MR to prioritize drug targets for their causal relevance for coronary heart disease (CHD). The targets were further prioritized using genetic co-localization, protein expression profiles from the Human Protein Atlas and, for targets with a licensed drug or an agent in clinical development, by sourcing data from the British National Formulary and clinicaltrials.gov. Out of the 341 drug targets identified through their association with circulating blood lipids (HDL-C, LDL-C and triglycerides), we were able to robustly prioritize 30 targets that might elicit beneficial treatment effects in the prevention or treatment of CHD. The prioritized list included NPC1L1 and PCSK9, the targets of licensed drugs whose efficacy has been already proven in clinical trials. To conclude, we discuss how this approach can be generalized to other targets, disease biomarkers and clinical end-points to help prioritize and validate targets during the drug development process. One Sentence SummaryWe provide genetic support for lipid-modifying drug targets for coronary heart disease prevention using drug target Mendelian randomization and further prioritization based on clinical and biological evidence.

genetics↗

bioRxiv2020

Accel-Align: A Fast Sequence Mapper and Aligner based on the Seed-Embed-Extend Method

BackgroundImprovements in sequencing technology continue to drive sequencing cost towards $100 per genome. However, mapping sequenced data to a reference genome remains a computationally-intensive task due to the dependence on edit distance for dealing with indels and mismatches introduced by sequencing. All modern aligners use seed-filter-extend (SFE) methodology and rely on filtration heuristics to reduce the overhead of edit distance computation. However, filtering has inherent performance-accuracy trade-offs that limits its effectiveness. ResultsMotivated by algorithmic advances in randomized low-distortion embedding, we introduce seed- embed-extend (SEE), a new methodology for developing sequence mappers and aligners. While SFE focuses on eliminating sub-optimal candidates, SEE focuses instead on identifying optimal candidates. To do so, SEE transforms the read and reference strings from edit distance regime to the Hamming regime by embedding them using a randomized algorithm, and uses Hamming distance over the embedded set to identify optimal candidates. To show that SEE performs well in practice, we present Accel-Align, an SEE-based short-read sequence mapper and aligner that is 3-12x faster than state-of-the-art aligners on commodity CPUs, without any special-purpose hardware, while providing comparable accuracy. ConclusionsAs sequencing technologies continue to increase read length while improving throughput and accuracy, we believe that randomized embeddings open up new avenues for optimization that cannot be achieved by using edit distance. Thus, the techniques presented in this paper have a much broader scope as they can be used for other applications like graph alignment, multiple sequence alignment, and sequence assembly. Availabilityhttps://github.com/raja-appuswamy/accel-align-release

bioinformatics↗

bioRxiv2020

Viral genome wide association study identifies novel hepatitis C virus polymorphisms associated with sofosbuvir treatment failure

Chronic hepatitis C virus (HCV) infection is a major cause of chronic liver disease, cirrhosis and hepatocellular carcinoma worldwide. With the recent development of direct acting antivirals (DAA), treatment of chronically infected patients has become highly effective although a subset of patients do not respond to therapy. Sofosbuvir is a common component of current de novo or salvage combination therapies. We used pre-treatment whole genome sequencing of HCV from 507 patients infected with HCV subtype 3a and treated with sofosbuvir containing regimens to detect viral polymorphisms associated with response to treatment. We found that three common polymorphisms present in HCV NS2 and NS3 proteins (not direct targets of sofosbuvir) were associated with reduced treatment response. These polymorphisms were enriched in post-treatment HCV sequences of patients unresponsive to treatment; they were also associated with lower reductions in viral load in the first week of therapy. The finding of polymorphisms in NS2 and NS3 proteins associated with poor treatment outcomes emphasises the value of more systematic genome-wide analyses of HCV in uncovering indirect but clinically relevant mechanisms of antiviral resistance.

microbiology↗

bioRxiv2019

Genomics of Human Respiratory Syncytial Virus Vaccine Attenuation

The human orthopneumovirus (HRSV) is a major cause of lower respiratory tract infection in children worldwide. Despite decades of efforts, no vaccine is available. In this work, we report mutations that are frequent in vaccine candidates and rare in wild-type genomes, taking into account all the publicly available HRSV sequence data. These mutations are different from the ones already known to attenuate the virus, and thus may contribute to the effort towards producing a live attenuated vaccine against HRSV.

genomics↗

bioRxiv2019

Data Resource Profile:The Dementias Platform UK (DPUK) Data Portal

The Dementias Platform UK (DPUK) Data Portal is a data repository facilitating access to data for 3 370 929 individuals in 42 cohorts. The Data Portal is an end-to-end data management solution providing a secure, fully auditable, remote access environment for the analysis of cohort data. All projects utilising the data are by default collaborations with the cohort research teams generating the data. The Data Portal uses UK Secure eResearch Platform (UKSeRP) infrastructure to provide three core utilities: data discovery, access, and analysis. These are delivered using a 7 layered architecture comprising: data ingestion, data curation, platform interoperability, data discovery, access brokerage, data analysis and knowledge preservation. Automated, streamlined, and standardised procedures reduce the administrative burden for all stakeholders, particularly for requests involving multiple independent datasets, where a single request may be forwarded to multiple data controllers. Researchers are provided with their own secure lab using VMware which is accessed using two factor authentication. Over the last 2 years, 160 project proposals involving 579 individual cohort data access requests were received. These were received from 268 applicants spanning 72 institutions (56 academic, 13 commercial, 3 government) in 16 countries with 84 requests involving multiple cohorts. Project are varied including multi-modal, machine learning, and Mendelian randomisation analyses. Data access is usually free at point of use although a small number of cohorts require a data access fee.

neuroscience↗

bioRxiv2019

Global variability of the human IgG glycome

Immunoglobulin G (IgG) is the most abundant serum antibody and is a key determinant of the humoral immune response. Its structural characteristics and effector functions are modulated through the attachment of various sugar moieties called glycans. IgG N-glycome patterns change with the age of individual and in different diseases. Variability of IgG glycosylation within a population is well studied and is affected by a combination of genetic and environmental factors. However, global inter-population differences in IgG glycosylation have never been properly addressed. Here we present population-specific N-glycosylation patterns of whole IgG, analysed in 5 different populations totalling 10,482 IgG glycomes, and of IgGs fragment crystallisable region (Fc), analysed in 2,530 samples from 27 populations sampled across the world. We observed that country of residence associates with many N-glycan features and is a strong predictor of monogalactosylation variability. IgG galactosylation also strongly correlated with the development level of a country, defined by United Nations health and socioeconomic development indicators. We found that subjects from developing countries had low IgG galactosylation levels, characteristic for inflammation and ageing. Our results suggest that citizens of developing countries may be exposed to country-specific environmental factors that can cause low-grade chronic inflammation and the apparent increase in biological age.

biochemistry↗

bioRxiv2018

Pervasive adaptation of hepatitis C virus to interferon lambda polymorphism across multiple genotypes

Genetic polymorphism in the interferon lambda (IFN-{lambda}) region is associated with spontaneous clearance of hepatitis C virus (HCV) infection and with response to interferon-based antiviral treatment. Here, we evaluate the associations between IFN- {lambda} polymorphism and HCV variation through a genome-to-genome analysis in 8,729 patients from diverse ancestral backgrounds infected with various HCV genotypes. We searched for associations between rs12979860 genotype, a tag for IFN-{lambda} haplotypes, and amino acid variants in the NS3, NS4A, NS5A and NS5B HCV proteins. We report multiple associations between host and pathogen variants in the full cohort as well as in subgroups defined by viral genotype and human ancestry. We also assess the combined impact of human and HCV variation on pre-treatment viral load. By demonstrating that IFN-{lambda} genetic variation leaves a large footprint in the viral genome, this study provides strong evidence of pervasive viral adaptation to host innate immune pressure during chronic HCV infection.

genomics↗

bioRxiv2018

Human genomics of acute liver failure due to hepatitis B virus infection: an exome sequencing study in liver transplant recipients

Acute liver failure (ALF) or fulminant hepatitis is a rare, yet severe outcome of infection with hepatitis B virus (HBV) that carries a high mortality rate. The occurrence of a life-threatening condition upon infection with a prevalent virus in individuals without known risk factors is suggestive of pathogen-specific immune dysregulation. In the absence of established differences in HBV virulence, we hypothesized that ALF upon primary infection with HBV could be due to rare deleterious variants in the human genome. To search for such variants, we performed exome sequencing in 21 previously healthy adults who required liver transplantation upon fulminant HBV infection and 172 controls that were positive for anti-HBc and anti-HBs antibodies but had no clinical history of jaundice or liver disease. After a series of hypothesis-driven filtering steps, we searched for putatively pathogenic variants that were significantly associated with case-control status. We did not find any causal variant or gene, a result that does not support the hypothesis of a shared monogenic basis for human susceptibility to HBV-related ALF in adults. This study represents a first attempt at deciphering the human genetic contribution to the most severe clinical presentation of acute HBV infection in previously healthy individuals.\n\nAuthor SummaryInfection with hepatitis B virus (HBV) is very common and causes a variety of liver diseases including acute and chronic hepatitis, cirrhosis and liver carcinoma. Acute HBV infection is often asymptomatic, still about 1% of newly infected people develop a rapid and severe disease known as acute liver failure or fulminant hepatitis. Acute liver failure has a high mortality rate and is an indication for urgent liver transplantation. It is not clear why some people, who are otherwise healthy, develop such severe symptoms upon infection with a common pathogen. Here, we hypothesized that rare DNA variants in the human genome could contribute to this unusual susceptibility. We sequenced the exome (i.e. the regions of the genome that encode the proteins) of 21 previously healthy adults who required liver transplantation upon fulminant HBV infection and searched for rare genetic variants that could explain the clinical presentation. We did not identify any variant that could be convincingly linked to the extreme susceptibility to HBV observed in the study participants. This suggests that HBV-induced acute liver failure is more likely to result from the combined influence of multiple genetic and environmental factors.

genomics↗

bioRxiv2018

HIV Peptidome-Wide Association Study Reveals Patient-Specific Epitope Repertoires Associated with HIV Control

Genetic variation in the peptide-binding groove of the highly polymorphic human leukocyte antigen (HLA) class I molecules has repeatedly been associated with HIV-1 control and progression to AIDS, accounting for up to 12% of the variation in HIV-1 set point viral load (spVL). This suggests a key role in disease control for HLA presentation of HIV-1 epitopes to cytotoxic T cells. However, a comprehensive understanding of the relevant HLA-bound HIV epitopes is still elusive. Here we developed a peptidome-wide association study (PepWAS) approach that integrates HLA genotypes and spVL data from 6,311 HIV-infected patients to interrogate the entire HIV-1 proteome (3,252 unique peptides) for disease-relevant peptides. This PepWAS approach revealed a core set of epitopes associated with spVL, including previously characterized epitopes but also several novel disease-relevant peptides. More importantly, each patient presents only 16 ({+/-}7) and 6 ({+/-}6) of these core epitopes through their individual HLA-B and HLA-A variants, respectively. Differences in these patient-specific epitope repertoires account for almost all the variation in spVL previously associated with HLA genetic variation. PepWAS thus enables a comprehensive functional interpretation of the robust but little understood association between HLA and HIV-1 control, prioritizing a short and targetable list of disease-associated epitopes for personalized immunotherapy.

genomics↗

bioRxiv2018

Lipoprotein Signatures of Cholesteryl Ester Transfer Protein and HMG-CoA Reductase Inhibition

BackgroundCETP inhibition reduces vascular event rates but confusion surrounds its low-density lipoprotein (LDL)-cholesterol effects. We sought to clarify associations of genetic inhibition of CETP on detailed lipoproteins.\n\nMethods and ResultsWe used variants associated with CETP (rs247617) and HMGCR (rs12916) expression in 62,400 Europeans with detailed lipoprotein profiling from nuclear magnetic resonance spectroscopy. Genetic associations were scaled to 10% lower risk of coronary heart disease (CHD). Associations of lipoprotein measures with risk of incident CHD in three population-based cohorts (770 cases) were examined.\n\nCETP and HMGCR had near-identical associations with LDL-cholesterol concentration estimated by Friedewald-equation. HMGCR had a relatively consistent effect on cholesterol concentrations across all apolipoprotein B-containing lipoproteins. CETP had stronger effects on remnant and very-low-density lipoprotein cholesterol but no effect on cholesterol concentrations in LDL defined by particle size (diameter 18-26 nm) (-0.02SD 95%CI: -0.10, 0.05 for CETP versus -0.24SD, 95%CI -0.30, -0.18 for HMGCR). CETP had profound effects on lipid compositions of lipoproteins, with strong reductions in the triglyceride content of all highdensity lipoprotein (HDL) particles. These alterations in triglyceride composition within HDL subclasses were observationally associated with risk of CHD, independently of total cholesterol and triglycerides (strongest HR per 1-SD higher triglyceride composition in very-large HDL 1.35; 95%CI: 1.18, 1.54).\n\nConclusionCETP inhibition does not affect size-specific LDL cholesterol but may lower CHD risk by lowering cholesterol in other apolipoprotein-B containing lipoproteins and lowering triglyceride content of HDL particles. Conventional composite lipid assays may mask heterogeneous effects of lipid-altering therapies.

genetics↗

bioRxiv2018

Sequence Alignment Through the Looking Glass

Rapid advances in sequencing technologies are producing genomic data on an unprecedented scale. The first, and often one of the most time consuming, step of genomic data analysis is sequence alignment, where sequenced reads must be aligned to a reference genome. Several years of research on alignment algorithms has led to the development of several state-of-the-art sequence aligners that can map tens of thousands of reads per second.\n\nIn this work, we answer the question \"How do sequence aligners utilize modern processors?\" We examine four state-of-the-art aligners running on an Intel processor and identify that all aligners leave the processor substantially underutilized. We perform an in-depth microarchitectural analysis to explore the interaction between aligner software and processor hardware. We identify bottlenecks that lead to processor underutilization and discuss the implications of our analysis on next-generation sequence aligner design.

bioinformatics↗

bioRxiv2018

Genetic factors and age are the strongest predictors of humoral immune responses to common pathogens and vaccines

IntroductionHumoral immune responses to infectious agents or vaccination vary substantially among individuals, and many of the factors responsible for this variability remain to be defined. Current evidence suggests that human genetic variation influences (i) serum immunoglobulin levels, (ii) seroconversion rates, and (iii) intensity of antigen-specific immune responses. Here, we evaluate the impact of intrinsic (age and sex), environmental and genetic factors on the variability of humoral response to common pathogens and vaccines.\n\nMethodsWe characterized the serological response to 15 antigens from common human pathogens or vaccines, in an age- and sex-stratified cohort of 1,000 healthy individuals (Milieu Interieur cohort). Using clinical-grade serological assays, we measured total IgA, IgE, IgG and IgM levels, as well as qualitative (serostatus) and quantitative IgG responses to cytomegalovirus, Epstein-Barr virus, herpes simplex virus 1 & 2, varicella zoster virus, Helicobacter pylori, Toxoplasma gondii, influenza A virus, measles, mumps, rubella, and hepatitis B virus. Following genome-wide genotyping of single nucleotide polymorphisms and imputation, we examined associations between ~5 million genetic variants and antibody responses using single marker and gene burden tests.\n\nResults and discussionWe identified age and sex as important determinants of humoral response, with older individuals and women having higher rates of seropositivity for most antigens. Genome-wide association studies revealed significant associations between variants in the human leucocyte antigen (HLA) class II region on chromosome 6 and anti-EBV and anti-rubella IgG levels. We used HLA imputation to fine map these associations to amino acid variants in the peptide-binding groove of HLA-DR{beta}1 and HLA-DP{beta}1, respectively. We also observed significant associations for total IgA levels with two loci on chromosome 2 and with specific KIR-HLA combinations.\n\nConclusionsUsing extensive serological testing and genome-wide association analyses in a well-characterized cohort of healthy individuals, we demonstrate that age, sex and specific human genetic variants contribute to inter-individual variability in humoral response. By highlighting genes and pathways implicated in the normal antibody response to frequently encountered antigens, these findings provide a basis to better understand disease pathogenesis.

genomics↗

bioRxiv2018

The Delirium and Population Health Informatics Cohort study protocol: ascertaining the determinants and outcomes from delirium in a whole population.

BackgroundDelirium affects 25% of older inpatients and is associated with long-term cognitive impairment and future dementia. However, no population studies have systematically ascertained cognitive function before, cognitive deficits during, and cognitive impairment after delirium. Therefore, there is a need to address the following question: does delirium, and its features (including severity, duration, and presumed aetiologies), predict long-term cognitive impairment, independent of cognitive impairment at baseline?\n\nMethodsThe Delirium and Population Health Informatics Cohort (DELPHIC) study is an observational population-based cohort study based in the London Borough of Camden. It is recruiting 2000 individuals aged [≥]70 years and prospectively following them for two years, including daily ascertainment of all inpatient episodes for delirium. Daily inpatient assessments include the Memorial Delirium Assessment Scale, the Observational Scale for Level of Arousal, and the Hierarchical Assessment of Balance and Mobility. Data on delirium aetiology is also collected. The primary outcome is the change in the modified Telephone Interview for Cognitive Status at two years.\n\nDiscussionDELPHIC is the first population sample to assess older persons before, during and after hospitalisation. The cumulative incidence of delirium in the general population aged [≥]70 will be described. DELPHIC offers the opportunity to quantify the impact of delirium on cognitive and functional outcomes. Overall, DELPHIC will provide a real-time public health observatory whereby information from primary, secondary, intermediate and social care can be integrated to understand how acute illness is linked to health and social care outcomes.

epidemiology↗

bioRxiv2017

Correcting for population stratification reduces false positive and false negative results in joint analyses of host and pathogen genomes

Studies of host genetic determinants of pathogen sequence variation can identify sites of genomic conflicts, by highlighting variants that are implicated in immune response on the host side and adaptive escape on the pathogen side. However, systematic genetic differences in host and pathogen populations can lead to inflated type I (false positive) and type II (false negative) error rates in genome-wide association analyses. Here, we demonstrate through simulation that correcting for both host and pathogen stratification reduces spurious signals and increases power to detect real associations in a variety of tested scenarios. We confirm the validity of the simulations by showing comparable results in an analysis of paired human and HIV genomes.

genomics↗