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Results for “Hidden Markov Models”

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PubMed2026

Statistical test to compare the linkage model and the admixture model based on central limit results.

In the Admixture Model, the probability that an individual carries a certain allele at a specific marker depends on the allele frequencies in K ancestral populations and the proportion of the individual's genome originating from these populations. The markers are assumed to be independent. The Linkage Model is a Hidden Markov Model that extends the Admixture Model by incorporating linkage between neighboring loci. We prove consistency and asymptotic normality of maximum likelihood estimators for the ancestry of individuals in the Linkage Model, complementing earlier results by (Pfaff et al., 2004; Pfaffelhuber and Rohde, 2022; Heinzel, 2025) for the Admixture Model. These results are used to prove that a statistical test that allows for model selection between the Admixture Model and the Linkage Model is an asymptotic level-α-test. Finally, we demonstrate the practical relevance of our results by applying the test to real-world data from The 1000 Genomes Project Consortium (2015).

Genetic Linkage↗

PubMed2026

Phlag: scalable detection of genomics regions with unexplained phylogenetic heterogeneity.

MOTIVATION: Phylogenetic analyses of entire genomes (phylogenomics) have revealed abundant heterogeneity of evolutionary histories. While much has been done to model this heterogeneity and to infer species trees despite it, the current toolkit has a limitation. Most methods assume that gene trees across the genome differ but are all sampled from the same distribution, defined by models such as the multi-species coalescent (MSC), and parametrized consistently across the genome. Empirical data strongly suggest this assumption is often violated because the species tree, its parameters, or the process generating the gene trees can all change across the genome. Errors in the data can further compound this heterogeneity. RESULTS: To address this challenge, we define the problem of detecting what segments of the genome are inconsistent with a putative species tree, even after allowing discordance according to MSC. We model gene trees not as a set, but rather as a series (a realization of a stochastic process) along genomic positions. We propose a Hidden Markov Model (HMM) approach applied to quartet statistics measured from gene trees and tie the model to MSC using simulations. The combined use of these three ideas leads to a scalable method called Phlag. On simulated and real data, we show that Phlag can detect many cases of change in underlying evolutionary processes, including reduced recombination rates, population size changes, and admixture, all using the same algorithm. AVAILABILITY AND IMPLEMENTATION: Phlag is available at github.com/bo1929/phlag. All results and scripts can be found at github.com/bo1929/shared.phlag.

Phylogeny↗

PubMed2026

Recovering membrane interaction kinetics of single molecules from 3D tracking data.

Interactions between cytosolic biomolecules and the bacterial inner membrane are fundamental to many cellular processes, yet directly measuring their binding kinetics in living cells remains challenging. Conventional 2D single-molecule tracking analyses can be insufficient, particularly when membrane association does not markedly alter the diffusion rate. Here, we present a method to recover membrane interaction kinetics from 3D single-molecule trajectories in rod-shaped bacteria. Using simulated 3D tracking data, we identify membrane-associated motion by quantifying how well short trajectory segments follow the circular curvature of the cell membrane. The resulting measure is further analyzed using a hidden Markov modeling framework, enabling robust discrimination between cytosolic and membrane-bound states and capturing the dynamics of state transitions without requiring diffusion-rate changes or direct colocalization with membrane markers. This work establishes a general framework for extracting membrane interaction kinetics from 3D single-molecule tracking data in live bacteria and highlights the value of realistic microscopy simulations for quantitative interpretation and systematic bias assessment.

Kinetics↗

PubMed2026

Nerpa 2: probabilistic linking of biosynthetic gene clusters to nonribosomal peptides.

MOTIVATION: Nonribosomal peptides (NRPs) are bioactive microbial metabolites with high pharmaceutical potential. Although genome mining enables large-scale detection of biosynthetic gene clusters (BGCs) predicted to encode NRPs, reliably linking these clusters to their chemical products remains challenging due to the flexible and heterogeneous organization of NRP assembly pathways. RESULTS: We present Nerpa 2, a probabilistic framework for accurate and scalable linking of NRP BGCs to candidate chemical structures. The method represents assembly lines as hidden Markov models (HMMs) that capture uncertainty and alternative biosynthetic routes. On curated datasets of experimentally validated BGC-product pairs, our tool outperforms existing methods in linking accuracy and pathway reconstruction. When applied to large genome mining datasets, Nerpa 2 efficiently identifies BGCs likely associated with known compounds and highlights potential producers of novel chemistry. AVAILABILITY AND IMPLEMENTATION: Nerpa 2 is freely available at https://github.com/gurevichlab/nerpa.

Multigene Family↗

PubMed2026

UPDhmm: detecting uniparental disomy from NGS trio data.

SUMMARY: Uniparental disomies (UPDs) are copy-neutral chromosomal alterations that occur when both copies of a chromosome pair (entire or segmental) come from one parent. UPDs, including isodisomies (identical parental chromosome) and heterodisomies (two different homologs from the same parent), reflect meiotic and/or mitotic aberrations of chromosomal segregation that can be associated with congenital or acquired disease. Despite their relevance, current methods to detect UPDs using sequence data (exomes or genomes) have limited sensitivity for small events, cannot precisely determine the UPD sub-type or coordinates, and perform poorly when including individuals or populations with consanguinity. We present UPDhmm, a novel tool that uses trio-based sequence data (proband and parents) and models inheritance patterns. UPDhmm predicts the most likely inheritance scenario, normal Mendelian inheritance versus UPD event, based on genotype combinations using a Hidden Markov Model (HMM). We validated the method using simulations on exome and genome data from 1000-Genomes projects. UPDhmm overperformed currently available methods in detecting simulated UPD events in both data types. We applied UPDhmm to a collection of nearly 2400 families with a proband with autism spectrum disorder (Simons Simplex Collection Project) and identified UPD events in two affected individuals, one of them previously unreported. These two events, a paternal isodisomy of chr8 and a maternal heterodisomy of chr22, can be genetic causes of the disease, demonstrating the clinical utility of UPDhmm. Thus, UPDhmm can facilitate the incorporation of UPD detection into clinical pipelines of genomic analysis. AVAILABILITY AND IMPLEMENTATION: UPDhmm is implemented in R and is available in the Bioconductor package (version 1.5.0): https://www.bioconductor.org/packages/release/bioc/html/UPDhmm.html. The source code can be found at https://github.com/martasevilla/UPDhmm under the MIT license.

Uniparental Disomy↗

PubMed2026

Phlag: Scalable detection of genomics regions with unexplained phylogenetic heterogeneity.

MOTIVATION: Phylogenetic analyses of entire genomes (phylogenomics) have revealed abundant heterogeneity of evolutionary histories. While much has been done to model this heterogeneity and to infer species trees despite it, the current toolkit has a limitation. Most methods assume that gene trees across the genome differ but are all sampled from the same distribution , defined by models such as the multi-species coalescent (MSC), and parametrized consistently across the genome. Empirical data strongly suggest this assumption is often violated because the species tree, its parameters, or the process generating the gene trees can all change across the genome. Errors in the data can further compound this heterogeneity. RESULTS: To address this challenge, we define the problem of detecting what segments of the genome are inconsistent with a putative species tree, even after allowing discordance according to MSC. We model gene trees not as a set, but rather as a series (a realization of a stochastic process) along genomic positions. We propose a Hidden Markov Model (HMM) approach applied to quartet statistics measured from gene trees and tie the model to MSC using simulations. The combined use of these three ideas leads to a scalable method called Phlag. On simulated and real data, we show that Phlag can detect many cases of change in underlying evolutionary processes, including reduced recombination rates, population size changes, and admixture, all using the same algorithm. AVAILABILITY AND IMPLEMENTATION: Phlag is available at github.com/bo1929/phlag . All results and scripts can be found at github.com/bo1929/shared.phlag .

Journal Article↗

PubMed2025

Annotation of RxLR Effectors in Oomycete Genomes.

Pathogens have evolved effector proteins to suppress host immunity and facilitate plant infections. RxLR effectors are small, secreted effector proteins with conserved RxLR and dEER amino acid motifs at the N terminus and highly variable C termini and are commonly found in oomycete species. We provide computational approaches to annotate RxLR candidate effector genes in a genome assembly in FASTA format with an available GFF file. Hidden Markov Modeling (HHM) is used in combination with regular expressions to search for RxLR and EER amino acid patterns.

Oomycetes↗

PubMed2026

A conserved distal-tail helical extension defines a tailspike attachment architecture in Gram-negative siphophages.

Rapid growth of bacteriophage genome collections has outpaced functional annotation of tail-tip proteins, limiting comparative analysis of host-recognition structures. Starting from a shared distal-tail gene organization in the Salmonella phages 9NA and Jersey, I developed a morphogenetic bioinformatic framework integrating gene synteny, sequence comparison, profile hidden Markov model (HMM) screening, structural evidence, structure-aware searching, and AlphaFold modeling. Comparison with the experimentally characterized lambda and Sf11 tail assemblies identified a predominantly alpha-helical C-terminal extension of the distal-tail (DT) protein associated with tailspike attachment, termed the distal-tail helical extension (DT-helix). Screening 541,986 proteins from 5167 complete NCBI RefSeq tailed-phage genomes, followed by evidence-based evaluation of sequence, genomic context, and structural architecture, identified 165 curated DT-helical-extension-associated phages. Their DT proteins segregated into six sequence groups. In the four principal multi-member groups, cognate tailspikes showed group-specific conservation in proximal N-terminal regions but substantially greater downstream diversity, consistent with sequence constraint at the DT-tailspike attachment boundary. A complementary ProstT5/Foldseek search supported the established groups but revealed no convincing additional highly divergent family. Together with the experimentally characterized Sf11 attachment interface, these findings define a recurrent morphogenetic architecture linking conserved distal-tail scaffolds to more variable receptor-binding proteins across siphophages infecting Gram-negative bacteria. Although universal exchangeability is not established, the identified scaffold-receptor-binding boundaries provide a framework for molecular characterization and rational phage engineering. Accession-level information for the 165 curated phages is available through PhageTailDB.

Viral Tail Proteins↗

PubMed2025

Predicting coarse-grained representations of biogeochemical cycles from metabarcoding data.

MOTIVATION: Taxonomic analysis of environmental microbial communities is now routinely performed thanks to advances in DNA sequencing. Determining the role of these communities in global biogeochemical cycles requires the identification of their metabolic functions, such as hydrogen oxidation, sulfur reduction, and carbon fixation. These functions can be directly inferred from metagenomics data, but in many environmental applications metabarcoding is still the method of choice. The reconstruction of metabolic functions from metabarcoding data and their integration into coarse-grained representations of biogeochemical cycles remains a difficult bioinformatics problem today. RESULTS: We developed a pipeline, called Tabigecy, which exploits taxonomic affiliations to predict metabolic functions constituting biogeochemical cycles. In a first step, Tabigecy uses the tool EsMeCaTa to predict consensus proteomes from input affiliations. To optimize this process, we generated a precomputed database containing information about 2404 taxa from UniProt. The consensus proteomes are searched using bigecyhmm, a newly developed Python package relying on Hidden Markov Models to identify key enzymes involved in metabolic function of biogeochemical cycles. The metabolic functions are then projected on coarse-grained representation of the cycles. We applied Tabigecy to two salt cavern datasets and validated its predictions with microbial activity and hydrochemistry measurements performed on the samples. The results highlight the utility of the approach to investigate the impact of microbial communities on biogeochemical processes. AVAILABILITY AND IMPLEMENTATION: The Tabigecy pipeline is available at https://github.com/ArnaudBelcour/tabigecy. The Python package bigecyhmm and the precomputed EsMeCaTa database are also separately available at https://github.com/ArnaudBelcour/bigecyhmm and https://doi.org/10.5281/zenodo.13354073, respectively.

Metagenomics↗

PubMed2025

Measurement and classification of bold-shy behaviours in medaka fish.

MOTIVATION: Boldness-shyness is considered a fundamental axis of behavioural variation in humans and other species, with obvious adaptive causes and evolutionary implications. Besides an individual's own genetics, this phenotype is also affected by the genetic make-up of peers in the individual's social environment. To identify genetic determinants of variation along the bold-shy behavioural axis, a reliable experimental and analytical set-up able to highlight direct and indirect genetic effects is needed. RESULTS: We describe a custom assay designed to detect bold-shy behaviours in medaka fish, combining an open-field and novel-object component. We use this assay to explore direct and social genetic effects on the behaviours of 307 pairs of fish from five inbred medaka strains. Applying a hidden Markov model (HMM) to classify behavioural modes, we find that direct genetic effects influence the proportions of time the five strains spent in slow-moving states, explaining up to 29.7% of the variance in time spent in those states. We also found that an individual's behaviour is influenced by the genetics of its tank partner, explaining up to 8.64% of the variance in the time spent in slow-moving states. Our behavioural assay in combination with the HMM analysis is applicable to follow-up genetic linkage studies of genetic variants involved in direct behavioural effects and indirect social genetic effects. A suitable genetic resource for such studies, the Medaka Inbred Kiyosu-Karlsruhe (MIKK) panel has recently been established. AVAILABILITY AND IMPLEMENTATION: The code associated with this work is available on GitHub (https://github.com/birneylab/medaka_behaviour_pilot) and Software Heritage (swh: 1: dir: c9abec1c5d62d22e43c9e97d995c56261784d9ab). Experimental data have been uploaded to the EBI Bioimage Archive (https://doi.org/10.6019/S-BIAD1421).

Animals↗

PubMed2026

Likelihood-based optimization enables accurate copy number estimation for paralogous genes using exome data.

MOTIVATION: Exome sequencing is widely used for genetic studies; however, accurate detection of copy number variants (CNV) in paralogous genes is challenging due to short-read mapping ambiguity and extensive copy-number variation. The human genome contains several hundred paralogous genes, many of which are known to harbor disease-associated CNVs. Existing exome CNV callers are primarily designed for rare CNV detection in uniquely mappable regions and are not well-suited for paralogous genes. METHODS: We describe a computational method (EdgeCopy) for copy number profiling of paralogous genes using whole-exome sequence data. EdgeCopy aggregates reads mapped to all copies of paralogous genes and relates observed read depth to copy number for multiple exome samples using an approximate composite likelihood function. The likelihood function is optimized using numerical optimization to obtain gene-level fractional copy number estimates that are discretized and refined using a Hidden Markov Model to obtain exon-level copy number estimates. RESULTS: Benchmarking of Edgecopy using experimental copy number data showed high concordance (mean = 0.973) for six disease-associated paralogous genes. We evaluated performance using whole-exome data from approximately 2400 samples across five continental populations from the 1000 Genomes Project. EdgeCopy shows robust concordance with whole-genome sequencing based estimates (0.974-0.982) across populations and 130 paralogous genes spanning a wide range of copy-number variation. In comparison, copy number analysis using a state-of-the-art exome CNV caller failed to estimate copy number for paralogous genes with very high mapping ambiguity and showed much lower concordance (0.565) for CNV events compared to EdgeCopy (0.908). AVAILABILITY: EdgeCopy is freely available at https://github.com/vibansal-lab/edgecopy.

Humans↗

PubMed2025

RRNPP quorum-sensing repertoires in the salivarius group genomes: overrepresentation and synchronous activation of SHP/Rgg systems in Streptococcus thermophilus.

UNLABELLED: In Bacillota, quorum sensing can be mediated by RRNPP regulators that are activated by autoinducing peptides (AIPs). In this study, we derived a hidden Markov model profile from a 3D-informed alignment to establish RRNPP repertoires for 527 genomes of streptococci in the salivarius group and identified probable AIPs. The salivarius group encompasses Streptococcus salivarius and Streptococcus vestibularis, which are part of the normal human oral microflora, and Streptococcus thermophilus, one of the most widely used bacteria in the dairy industry. We observed a large amount of plasticity in these repertoires, as well as profound differences among species. Notably, S. salivarius displayed an accumulation of ComR regulators, while S. thermophilus displayed an accumulation of Rgg regulators. The latter family included SHP-associated Rgg regulators, systems in which SHPs serve as AIPs; most of these regulators control the production of post-translationally modified peptides (RaS-RiPPs). Their level of richness contrasts with the genome reduction that accompanied S. thermophilus' adaptation to milk. We then used liquid chromatography-high resolution tandem mass spectrometry to analyze the activity of the eight most common SHP/Rgg systems by characterizing the SHPs and RaS-RiPPs found in the supernatants. We detected four SHPs and one RaS-RiPP that have never been seen before in S. thermophilus, and we showed that seven of the eight SHP/Rgg systems were functional. Finally, by simultaneously monitoring the amounts of both the SHPs and RaS-RiPPs, we demonstrated that the fates of these two peptide types differed during growth. SHP presence in the supernatant was transient, a pattern likely related to the peptides' signaling role. IMPORTANCE: Streptococcus thermophilus possesses an unusually high number of Rgg regulators, which are activated by SHP pheromones that control the production of RaS-RiPPs, peptides with cyclization motifs and growth inhibition properties. We conducted an in silico analysis of regulator repertoires across a wide range of strains; a subsequent experimental study revealed that the majority of the SHP/Rgg systems were functional. Employing an optimized liquid chromatography-high resolution tandem mass spectrometry protocol, we were able to better detect and follow SHP and RaS-RiPP accumulation. While RaS-RiPPs accumulated during growth, SHPs were only transiently present in the extracellular environment. This observation suggests that we could manipulate quorum sensing by adding SHPs to the growth medium and highlights the need to study the functions of the RaS-RiPPs.

Streptococcus thermophilus↗

PubMed2026

Landscape of retron diversity across the SPIRE microbial metagenome resource reveals candidate novel type XI-like lineages.

Retrons are bacterial genetic elements encoding a specialized reverse transcriptase (RT) that synthesizes multicopy single-stranded DNA and are increasingly recognized as components of bacterial anti-phage defense systems. However, their diversity and ecological distribution across large-scale genomic resources remain poorly characterized. Here, we surveyed retron RTs across the SPIRE representative metagenome collection, a non-redundant, species-level data set spanning diverse microbial habitats. Using a curated panel of type-specific hidden Markov models, we identified retrons representing all canonical types together with additional divergent lineages. Retron distribution showed strong taxonomic and ecological structuring, with some groups restricted to specific bacterial phyla, whereas others were broadly distributed across environmental categories. Systematic novelty assessment identified two candidate type XI-like lineages, TXI_C2like and TXI_noncan_h, characterized by protease-independent architectures and distinct accessory modules associated with WYL- and DnaB_C-containing proteins, respectively. De novo covariance-based analyses further identified candidate msr/msd-like non-coding RNA structures in both lineages, supporting conservation of the canonical RT-ncRNA organizational framework despite extensive sequence divergence. Together, these findings expand the known diversity of retron systems and identify type XI-like retrons as a dynamic and previously underexplored evolutionary group.IMPORTANCERetrons are bacterial genetic elements that are increasingly exploited as programmable tools for genome editing, molecular recording, and biosensing in addition to their natural role in anti-phage defense. Despite this growing biotechnological interest, the true diversity of retrons across the bacterial world has remained largely unmapped. By mining a resource of over 100,000 processed microbial metagenomes, we uncovered thousands of retron sequences spanning known types as well as previously unrecognized lineages and found that their distribution is strongly shaped by both bacterial taxonomy and ecological niche. Among these, we identified two candidate new lineages related to type XI retrons that lack the protease domain typical of this group but instead carry distinct accessory proteins, expanding the known architectural diversity of these systems. These findings broaden the catalog of retron diversity available for functional characterization and biotechnological engineering and provide a framework for prioritizing candidate lineages for future experimental validation.

effectors↗

PubMed2026

Deciphering the mosaic genome of sugarcane cultivars through polyploid admixture inference with AdmixPoly.

BACKGROUND: Characterizing population structure and admixture events between ancestral groups plays a key role in understanding the evolutionary history of species and crops. Most tools for inferring admixture have been developed for diploids and are not suitable for polyploids, in particular those with high and mixed ploidy such as Saccharum. RESULTS: Here we present AdmixPoly, an R-package designed to infer admixture in polyploid species both at the genome-wide scale and locally along chromosomes. We compare AdmixPoly with state-of-the-art methods using simulations, demonstrating its precision and computational efficiency. Notably, local admixture inference in complex scenarios, such as high ploidy levels, large numbers of ancestral groups and alleles per marker is enabled through efficient approximations of emission and transition probabilities within a hidden Markov model framework. We apply this approach to characterize the contributions of wild Saccharum species to the complex polyploid genome of modern sugarcane cultivars. A panel of wild and cultivated Saccharum accessions is genotyped for 80K genomic regions, each revealing approximately 50 read-scale haplotypes. CONCLUSIONS: The results reveal that most of the approximately 12 copies of each basic chromosome in modern cultivars are derived from the domesticated species Saccharum officinarum, with one to four copies typically contributed by distinct subgroups of the wild species Saccharum spontaneum. In addition, contributions from an unknown wild Saccharum group originating from the Pacific were identified in most cultivars. The conserved pattern of these introgressions suggests that they can be traced back to the early stages of sugarcane breeding approximately a century ago.

Saccharum↗

PubMed2026

Genome-Wide Identification and Bioinformatics Analysis of the FAD Gene Family in Walnut (Juglans regia L.).

Fatty acid desaturase (FAD) is a core catalytic enzyme in plants for the synthesis of unsaturated fatty acids, profoundly affecting plant growth, development, and adaptability to various environmental stresses. The walnut (Juglans regia L.) is an important woody oil tree species, and its kernel is rich in unsaturated fatty acids. Systematic identification of the walnut FAD gene family and analysis of its function are of great significance for revealing the molecular mechanisms underlying unsaturated fatty acid metabolism in the walnut. Based on walnut whole-genome data, this study used homology alignment and hidden Markov model search methods to identify the JrFAD gene family members. Subsequently, a variety of bioinformatics tools were used to systematically analyze their structural characteristics, evolutionary expansion mechanism, expression regulation, and function. A total of 21 JrFAD gene family members were identified and classified into five subfamilies. The family genes were unevenly distributed on nine chromosomes. WGD/segmental duplication was the main expansion method, and the duplicated gene pairs experienced strong purification selection. The family gene promoter sequence is rich in regulatory elements that respond to light, plant hormones, and various stresses. The expression pattern analysis showed that JrFAD3.1 and JrFAD2.3 showed high expression specifically during the rapid accumulation of walnut kernel oil. This study clarified the composition and evolutionary characteristics of the FAD gene family in the walnut, which provides useful information for in-depth analyses of its functional mechanism in the regulation of lipid metabolism, and also identified potential candidate gene resources for the genetic improvement of walnut varieties with high amounts of unsaturated fatty acids.

Juglans↗

PubMed2025

Golgi_traff phylogeny reveals ancient eukaryotic genes with recent surprises: replication and diversification of HID1 domain-containing protein unique to Schizosaccharomyces.

Golgi_traff is a Pfam clan containing two members, Dymeclin (DYM) and HID1 domain-containing protein (HID). Interrogation of over 900 eukaryotic genomes with sequence models showed that both are ancient eukaryotic genes, which have exhibited different paths of gene loss, including from major taxonomic groups. For example, the Metazoa have both genes, whereas the Viridiplantae and Dikarya have lost HID and DYM, respectively. A unique replication event occurred within the genus Schizosaccharomyces in that all sequenced species possess three HID-encoding paralogs, whereas its nearest fungal relatives and other eukaryotes are almost exclusively monogenic. A phylogenetic analysis of yeasts revealed that the Golgi-resident paralog Human ortholog 3 (SPAC17A5.16) is more similar to the HID of other yeasts than to its paralogs. Transmission electron microscopy revealed that the SPAC17A5.16 mutant lacks a stacked Golgi apparatus (GA) form, suggesting a role in maintaining GA structure. Altered proliferation of the SPAC17A5.16 mutant in response to GA disrupting chemical agents indicated a perturbation of GA-related functions. Structural models suggest SPAC17A5.16 has a long, disordered N-terminal region that may facilitate anchoring to GA membranes. A modification to Schizosaccharomyces HID nomenclature is proposed to reflect their evolutionary and functional characteristics. The potential of the Golgi_traff clan to serve as a model for the diversification of protein function according to the concepts of sub/neofunctionalization is discussed.

Schizosaccharomyces↗

PubMed2019

A systematic capsid evolution approach performed in vivo for the design of AAV vectors with tailored properties and tropism.

Adeno-associated virus (AAV) capsid modification enables the generation of recombinant vectors with tailored properties and tropism. Most approaches to date depend on random screening, enrichment, and serendipity. The approach explored here, called BRAVE (barcoded rational AAV vector evolution), enables efficient selection of engineered capsid structures on a large scale using only a single screening round in vivo. The approach stands in contrast to previous methods that require multiple generations of enrichment. With the BRAVE approach, each virus particle displays a peptide, derived from a protein, of known function on the AAV capsid surface, and a unique molecular barcode in the packaged genome. The sequencing of RNA-expressed barcodes from a single-generation in vivo screen allows the mapping of putative binding sequences from hundreds of proteins simultaneously. Using the BRAVE approach and hidden Markov model-based clustering, we present 25 synthetic capsid variants with refined properties, such as retrograde axonal transport in specific subtypes of neurons, as shown for both rodent and human dopaminergic neurons.

barcoding↗

PubMed2026

HiCPotts: An R/Bioconductor package to identify significant interactions in chromosome conformation capture data and model sources of bias.

MOTIVATION: Chromosome Conformation Capture methods, including Hi-C, micro-C or Capture-C, are used to map chromatin interactions genome-wide. Most of the existing computational methods do not account for sources of bias (such as DNA accessibility, GC content or TE content) in the data. RESULTS: We previously developed ZipHiC, a Bayesian method based on the hidden Markov random field (HMRF) model and the Approximate Bayesian Computation (ABC), that uses zero-inflated Poisson distribution to model the noise, signal and false signal of the data and showed that this approach was able to detect bias from DNA accessibility, GC content and TE content in both Hi-C and micro-C data. Here, we present HiCPotts, another Bayesian method based on the HMRF model and the ABC that uses a zero-inflated Negative Binomial distribution instead to model the noise and signal of the data. We systematically show that HiCPotts reduces false positives and increases recovery of true interactions compared to ZipHiC, but also compared to other methods such as FastHiC, Juicer and HiCExplorer. Most importantly, we provide an R/Bioconductor package that allows modelling the noise, signal and false signal using various distributions such as the zero-inflated Negative Binomial (ZINB) and the zero-inflated Poisson distribution (ZIP). AVAILABILITY AND IMPLEMENTATION: https://bioconductor.org/packages/HiCPotts/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Approximate Bayesian Computation↗