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At least 19 recordsLinked to original sources

Uchimata: a toolkit for visualization of 3D genome structures on the web and in computational notebooks.

SUMMARY: Uchimata is a toolkit for visualization of 3D structures of genomes. It consists of two packages: a Javascript library facilitating the rendering of 3D models of genomes, and a Python widget for visualization in Jupyter Notebooks. Main features include an expressive way to specify visual encodings, and filtering of 3D genome structures based on genomic semantics and spatial aspects. Uchimata is designed to be highly integratable with biological tooling available in Python. AVAILABILITY AND IMPLEMENTATION: Uchimata is released under the MIT License. The Javascript library is available on NPM, while the widget is available as a Python package hosted on PyPI. The source code for both is available publicly on Github (https://github.com/hms-dbmi/uchimata and https://github.com/hms-dbmi/uchimata-py) and Zenodo (https://doi.org/10.5281/zenodo.17831959 and https://doi.org/10.5281/zenodo.17832045). The documentation with examples is hosted at https://hms-dbmi.github.io/uchimata/.

Software

Uchimata: a toolkit for visualization of 3D genome structures on the web and in computational notebooks.

SUMMARY: Uchimata is a toolkit for visualization of 3D structures of genomes. It consists of two packages: a Javascript library facilitating the rendering of 3D models of genomes, and a Python widget for visualization in Jupyter Notebooks. Main features include an expressive way to specify visual encodings, and filtering of 3D genome structures based on genomic semantics and spatial aspects. Uchimata is designed to be highly integratable with biological tooling available in Python. AVAILABILITY AND IMPLEMENTATION: Uchimata is released under the MIT License. The Javascript library is available on NPM, while the widget is available as a Python package hosted on PyPI. The source code for both is available publicly on Github (https://github.com/hms-dbmi/uchimata and https://github.com/hms-dbmi/uchimata-py). The documentation with examples is hosted at https://hms-dbmi.github.io/uchimata/. CONTACT: david_kouril@hms.harvard.edu or nils@hms.harvard.edu.

Journal Article

Integrative modeling of the genome structure and dynamics in fission yeast.

Genome organization in the nucleus is highly structured and dynamic. Recent advances in genomic technology have enabled the measurement of genome-wide architecture and locus-specific motion, yielding contact maps and live-cell trajectories. However, these outcomes are derived from different modalities and are not directly comparable, with their quantitative integration being a key challenge. Here we establish a genome-wide live-cell imaging platform in fission yeast Schizosaccharomyces pombe, tracking 131 chromosomal loci, along with the spindle pole body (SPB) and nucleolus, to construct a quantitative map of locus dynamics. By integrating these dynamics with contact data through polymer modeling of Hi-C data, we build a physics-based "digital twin" of the S. pombe genome consistent with the spatiotemporal dynamics of interphase chromatin. We validate it against genome-wide mobility patterns and known architectural features, including centromere and telomere clustering. The model also identifies distinct dynamical regimes: centromere- and telomere-proximal loci relax within [Formula: see text]150 s, whereas the remaining loci relax within [Formula: see text]70 s. We measure semiperiodic dynamics of SPB motion, including a characteristic peak near 225 s and [Formula: see text] fluctuations. We use the model with SPB-directed forcing to show how these low-frequency components propagate through the genome to drive genome-wide chromatin displacements. Together, this predictive physics-based modeling framework integrates genome structure and dynamics to reveal how nuclear mechanical driving forces shape chromosome motion, linking mechanically driven chromatin responses to genome maintenance and regulation.

Schizosaccharomyces

Exploring the shared genetic architecture of sarcopenia using genomic structural equation modeling.

Sarcopenia is a common age-associated condition characterized by the progressive loss of skeletal muscle mass, strength, and physical functionality. While large-scale genome-wide association studies (GWAS) have previously addressed isolated traits of sarcopenia, the multifactorial genetic architecture underlying this condition remains largely undefined. To characterize the common genetic basis of sarcopenia-related traits, genomic structural equation modeling (Genomic-SEM) was implemented. Multiple post-GWAS analytic approaches were integrated to pinpoint susceptibility loci. These analyses encompassed identifying enriched genetic pathways and relevant genomic elements, as well as cell-type-specific enrichment in skeletal muscle satellite stem cells, mesenchymal stem cells, and skeletal muscle satellite cells in limb muscle. Furthermore, based on the integrated GWAS data of sarcopenia-related traits, polygenic risk score (PRS) analysis was conducted to evaluate risk associations at the chromosomal level. A well-fitted Genomic-SEM successfully integrated the GWAS data, revealing the shared genetic architecture of sarcopenia-related traits. We identified 110 single nucleotide polymorphisms (SNPs) reaching genome-wide significance (p&#x2009;<&#x2009;5&#x2009;&#xd7;&#x2009;10-8), of which 9 represent novel discoveries. Subsequent fine-mapping procedures and gene-set analyses identified 15 causal variants alongside 77 candidate susceptibility genes. This study provides a comprehensive genetic characterization of sarcopenia via Genomic-SEM, offering new insights into the etiological pathways underlying sarcopenia.

Sarcopenia

Genomic Structural Equation Modeling Identifies a Shared Inflammatory Genetic Dimension Across Inflammatory Arthritis Phenotypes and Biomarkers.

BACKGROUND: Inflammatory arthritis (IA), including rheumatoid arthritis (RA), psoriatic arthritis (PsA) and gout, shares systemic inflammatory features indexed by C-reactive protein (CRP) and interleukin-6 (IL-6), yet the extent of their common genetic basis remains unclear. AIMS: We aimed to delineate the shared genetic architecture across IA phenotypes and inflammatory biomarkers. MATERIALS AND METHODS: We applied genomic structural equation modelling (Genomic SEM) to GWAS summary statistics for RA, PsA, gout, CRP and IL-6, fitted a single common factor, and performed multivariate GWAS followed by fine-mapping, transcriptome-wide association, gene-based analysis, pathway enrichment, and cell-type and spatial mapping. RESULTS: A single common factor was fitted (CFI = 0.990, SRMR = 0.045). The multivariate GWAS identified 56 genome-wide significant SNPs across 10 independent lead loci, including one novel signal. Fine-mapping prioritized high-confidence variants near PTPN22, the CRP gene cluster and a urate-associated locus. Gene-level analyses converged on DCLRE1B, PTPN22, IL6R, NLRP3 and HNF1A, with pathway enrichment implicating inflammasome assembly and metabolic-inflammatory overlap. Cell-type enrichment highlighted myeloid populations, and spatial mapping localized signals to lung, kidney, mucosal epithelium and gastrointestinal tissues. DISCUSSION: These results delineate a shared inflammatory genetic dimension across IA phenotypes and biomarkers, anchored in immune, inflammasome, cytokine-receptor and metabolic pathways. CONCLUSION: Together, these findings provide a valuable framework for prioritizing candidate genes and cellular contexts for future investigation.

TWAS

Revealing the Shared Genetic Architecture of Metabolic Dysfunction-Associated Steatotic Liver Disease-Related Traits Through Genomic Structural Equation Modeling.

Although individual traits related to metabolic dysfunction-associated steatotic liver disease (MASLD) have been investigated through large-scale genome-wide association studies (GWASs), the shared genetic susceptibility across these traits remains unclear. We therefore conducted a multivariate GWAS of key MASLD-related traits to elucidate their common genetic architecture. We applied genomic structural equation modeling to model a latent genetic factor (MASLD-F) underlying genetically correlated MASLD-related traits, leveraging their GWAS-derived genetic correlations. We then performed functional annotations, including fine-mapping, transcriptome-wide association study, and cell- and tissue-type-specific enrichment analyses, and conducted Mendelian randomization analyses to identify modifiable risk factors. Our multivariate MASLD-F GWAS identified 50 independent variants across 48 genomic loci. Transcriptomic imputation identified several MASLD-F-associated genes, including ARNTL, NPC1, BTBD10, VDAC2, TSKU, SFMBT1, and ABHD17C. We observed significant enrichment of MASLD-F-related genetic signals predominantly in brain tissues, pancreatic islets, and the adrenal gland. Additionally, six modifiable risk factors and four modifiable protective factors for MASLD-F were identified. These findings reveal a complex shared genetic architecture underlying MASLD components, thereby expanding our understanding of disease pathogenesis and providing novel insights for precision medicine and public health interventions.

Humans

Genomic structural equation modeling elucidates the shared genetic architecture of allergic disorders.

BACKGROUND: The intricate shared genetic architecture underlying allergic disorders-including allergic asthma, atopic dermatitis, contact dermatitis, allergic rhinitis, allergic conjunctivitis, allergic urticaria, anaphylaxis, and eosinophilic esophagitis-remains incompletely characterized. METHODS: Our study employed genomic structural equation modeling (Genomic SEM) to define the common factor representing the shared genetic architecture of allergic disorders. Coupled with diverse post-GWAS analytical methods, we aimed to discover susceptible loci and investigate genetic associations with external traits. Furthermore, we explored enriched genetic pathways, cellular layers, and genomic elements, and investigated putative plasma protein biomarkers. Polygenic risk score (PRS) analyses, leveraging our integrated GWAS data, were conducted to assess chromosomal-level risk associations for allergic disorders. RESULTS: A well-fitted genomic SEM integrated GWAS data, revealing the shared genetic architecture of allergic disorders. We identified a total of 2038 genome-wide significant SNP loci (p&#x2009;<&#x2009;5e-8), including 31 previously unreported loci. Fine-mapping of variants and gene sets pinpointed 2 causal variants and 31 candidate susceptible genes. Genetic correlation analyses further illuminated the shared genetic architecture underlying multiple traits, notably psychiatric disorders. Preliminary findings identified four putative causal plasma protein biomarkers. CONCLUSION: Notably, this study presents the first comprehensive genetic characterization of allergic disorders through a GWAS analysis of an unmeasured composite phenotype, providing novel insights into shared etiological pathways across these conditions.

Humans

Structural genomics sheds light on protein functions and remote homologs across the insect tree of life.

Protein structure bridges the sequence-function relationship, enabling deep exploration of biological processes across diverse organisms. Insects, the most diverse animal lineage, accounting for over 50% of all described animal species, provide an exceptional system for exploring sequence-structure-function relationships. Here, we reconstructed a comprehensive and well-resolved phylogeny of 4854 insects, spanning all orders. Leveraging this framework, we created an atlas of 13.29 million predicted protein structures from 824 representative species, including 11.63 million newly predicted structures. Structural clustering revealed that proteins with divergent sequences but similar structures could be effectively grouped together. Structural similarity searches against proteins with well-characterized functions yielded annotations for 7.61 million insect proteins, including up to 14% of previously unannotated proteins. We further identified 750 million remote homologs between insect proteins, many of which trace back to ancient branches of the insect phylogeny. Remarkably, despite extensive sequence divergence, cGAS-like receptors (cGLRs) were structurally conserved across all 824 insects. Experimental assays demonstrated that these structurally identified cGLRs play a crucial role in antiviral defense in the yellow fever mosquito. Our findings highlight the significance of structural genomics for understanding protein function and evolution across the tree of life.

Animals

Rok from B. subtilis: Bridging genome structure and transcription regulation.

Bacterial genomes are folded and organized into compact yet dynamic structures, called nucleoids. Nucleoid orchestration involves many factors at multiple length scales, such as nucleoid-associated proteins and liquid-liquid phase separation, and has to be compatible with replication and transcription. Possibly, genome organization plays an intrinsic role in transcription regulation, in addition to classical transcription factors. In this review, we provide arguments supporting this view using the Gram-positive bacterium Bacillus subtilis as a model. Proteins BsSMC, HBsu and Rok all impact the structure of the B. subtilis chromosome. Particularly for Rok, there is compelling evidence that it combines its structural function with a role as global gene regulator. Many studies describe either function of Rok, but rarely both are addressed at the same time. Here, we review both sides of the coin and integrate them into one model. Rok forms unusually stable DNA-DNA bridges and this ability likely underlies its repressive effect on transcription by either preventing RNA polymerase from binding to DNA or trapping it inside DNA loops. Partner proteins are needed to change or relieve Rok-mediated gene repression. Lastly, we investigate which features characterize H-NS-like proteins, a family that, at present, lacks a clear definition.

Bacillus subtilis

Unicorn: enhancing single-cell Hi-C data with blind super-resolution for 3D genome structure reconstruction.

MOTIVATION: Single-cell Hi-C (scHi-C) data provide critical insights into chromatin interactions at individual cell levels, uncovering unique genomic 3D structures. However, scHi-C datasets are characterized by sparsity and noise, complicating efforts to accurately reconstruct high-resolution chromosomal structures. In this study, we present ScUnicorn, a novel blind super-resolution framework for scHi-C data enhancement. ScUnicorn uses an iterative degradation kernel optimization process, unlike traditional super-resolution approaches, which rely on downsampling, predefined degradation ratios, or constant assumptions about the input data to reconstruct high-resolution interaction matrices. Hence, our approach more reliably preserves critical biological patterns and minimizes noise. Additionally, we propose 3DUnicorn, a maximum likelihood algorithm that leverages the enhanced scHi-C data to infer precise 3D chromosomal structures. RESULTS: Our evaluation demonstrates that ScUnicorn achieves superior performance over the state-of-the-art methods in terms of Peak Signal-to-Noise Ratio, Structural Similarity Index Measure, and GenomeDisco scores. Moreover, 3DUnicorn's reconstructed structures align closely with experimental 3D-FISH data, underscoring its biological relevance. Together, ScUnicorn and 3DUnicorn provide a robust framework for advancing genomic research by enhancing scHi-C data fidelity and enabling accurate 3D genome structure reconstruction. AVAILABILITY AND IMPLEMENTATION: Unicorn implementation is publicly accessible at https://github.com/OluwadareLab/Unicorn.

Single-Cell Analysis

Genomic structure of class 1 and 2 integrons in non-typhoidal Salmonella isolated from food animals and related meat products in the USA.

OBJECTIVES: Integrons facilitate the capture and expression of exogenous genes, including antimicrobial resistance (AMR) genes. This study aimed to detect the presence of integrons, examine their genomic structure and location, and analyse integron-associated AMR, virulence and stress response genes in Salmonella using WGS. METHODS: WGS data from 193 Salmonella strains, representing 38 serotypes isolated from food animals and related meat products (2001-2019), were analysed using bioinformatic tools to assess integron presence and characterize their genomic architectures. RESULTS: Of 193 isolates, 116 (60.1%) harboured class 1 and/or class 2 integrons. Class 1 integrons alone were detected in 105 isolates, with some containing multiple copies. One S. Infantis isolate harboured only class 2 integrons, whereas 10 others contained both classes. No class 3-5 integrons were found. Twenty-seven class 1 integrons were chromosomal; the rest were plasmid-associated, linked to various plasmid incompatibility (Inc) types. Sixty-nine distinct AMR genes conferring resistance to 11 antimicrobial classes were found in integron cassettes or integron-associated plasmids. Genes linked to resistance to quaternary ammonium compounds and heavy metals, as well as ISs and transposons, were also identified. Significant virulence and stress response genes and proteins such as groES-groEL, LysR and EAL (glutamate, alanine and leucine) were common in integron cassettes. CONCLUSIONS: Class 1 integrons are prevalent in MDR Salmonella isolates from food animals and related meat products and are linked to diverse plasmid types. Their association with AMR, virulence and stress response genes underscores their role in AMR dissemination, and bacterial adaptation and pathogenicity.

Integrons

"Tissue-specific mitochondrial dysfunction in keratoconus: An integrated structural, genomic, and functional analysis".

PURPOSE: Keratoconus (KC) is a progressive corneal ectasia characterized by stromal thinning, conical protrusion, and irregular astigmatism, leading to visual impairment. Although oxidative stress is implicated in KC, the role of mitochondrial dysfunction remains unclear. We evaluated mitochondrial structural, genomic, and functional abnormalities in corneal tissues and blood from KC patients. METHODS: This prospective study enrolled 110&#x202f;KC patients and 55 controls. Transmission electron microscopy (TEM) and immunohistochemistry (IHC) were performed on epithelial and stromal tissues from 10&#x202f;KC to 5 control corneas assessing mitochondrial morphology, oxidative phosphorylation (OXPHOS) complexes and pro-apoptotic protein NOXA. Whole mitochondrial DNA (mtDNA) sequencing and relative mtDNA copy number analysis were performed on paired blood and corneal tissues from 50&#x202f;KC patients and 35 controls including both epithelial and stromal samples. Gene expression of mitochondrial biogenesis and oxidative stress-related genes was analysed by qRT-PCR in corneal epithelium from independent 50&#x202f;KC patients and 15 controls. RESULTS: TEM revealed cristolysis, membrane disruption, and reduced mitochondrial density in KC corneas. IHC showed reduced expression of OXPHOS complexes and increased NOXA expression (p&#x202f;<&#x202f;0.05). Sequencing identified 1107 mtDNA variants, with more variants in corneal tissues than matched blood (929 vs. 576; p&#x202f;=&#x202f;0.0002). Recurrent likely pathogenic variants were enriched in complex I-encoding genes (ND4, ND5). KC corneas showed reduced mtDNA copy number, downregulated POLRMT, upregulated NOX4, and significant downregulation of multiple antioxidant genes (p&#x202f;<&#x202f;0.0001). CONCLUSION: KC patients exhibit tissue-specific mitochondrial abnormalities and impaired oxidative stress regulation, supporting a role for mitochondrial dysfunction in disease pathogenesis and highlighting potential therapeutic targets.

Corneal pathology

Generating three-dimensional genome structures with a variational quantum algorithm.

Chromosome conformation capture experiments have revealed the underlying spatial interactions that govern three-dimensional (3D) genome organization and topology. Detecting 3D contacts between genomic loci considerably enhances our understanding of fundamental regulatory processes. Modeling 3D structures from experimental contact matrices can further contextualize the relationship between 3D genome organization and regulation. While classical algorithms have been successful in reconstructing genomic conformations, we investigate the prospect of quantum computation to aid in modeling the conformational space. In this context, we propose a novel variational quantum algorithm (VQA) to model the distribution of 3D genomic structures from experimental contact data. Through rigorous evaluations, we demonstrate the capability of our algorithm to sample ensembles of viable 3D conformations that agree well with experimental and simulated contact data. Furthermore, we extend our methodology to model the conformational space of a single cell or a population of cells. In the advent of sufficient quantum utility, the insights gained from this study can serve as a foundation for investigating high-resolution, large-scale ensembles of genomic conformations through generative VQAs.

Algorithms

Hidden genomic structure and widespread structural polymorphism across environmental gradients in the spiny sea star Marthasterias glacialis.

Genomic regions of reduced recombination can preserve linkage among co-adapted alleles, facilitating local adaptation despite high connectivity. Such regions-often generated by chromosomal inversions-may be especially important in highly dispersive marine taxa yet remain poorly documented in echinoderms. Here, we combined a chromosome-level reference genome with genome-wide ddRAD-seq from 296 Marthasterias glacialis individuals across 19 Atlantic-Mediterranean locations to quantify population structure and scan for recombination-suppressed haploblocks. Genome-wide neutral markers showed significant population differentiation together with evidence of high connectivity, revealed by the presence of inter-ecoregion migrants. Additionally, we identified 16 polymorphic haploblocks with patterns consistent with putative chromosomal inversions spanning 18.6% of the genome. Haploblock haplotypes were strongly environmentally and geographically structured and contained genes with key functions in stress response, osmoregulation and thermal tolerance. Haplotype distributions also paralleled previously described mitochondrial lineages despite nuclear gene flow, consistent with a model of ancient divergence followed by secondary contact. Overall, our results suggest a role for widespread structural polymorphism in adaptive differentiation in Echinodermata, providing a framework for linking echinoderm genome rearrangements to ecological divergence. Marthasterias glacialis thus emerges as a promising system to explore how structural variation contributes to adaptation and genome evolution in highly dispersive organisms.

Animals

Chromosome-scale assembly with improved annotation provides insights into breed-wide genomic structure and diversity in domestic cats.

INTRODUCTION: Comprehensive genomic resources offer insights into biological features, including traits/disease-related genetic loci. The current reference genome assembly for the domestic cat (Felis catus), Felis_Catus_9.0 (felCat9), derived from sequences of the Abyssinian cat, may inadequately represent the general cat population, limiting the extent of deducible genetic variations. OBJECTIVES: The goal was to develop Anicom American Shorthair 1.0 (AnAms1.0), a reference-grade chromosome-scale cat genome assembly. METHODS: In contrast to prior assemblies relying on Abyssinian cat sequences, AnAms1.0 was constructed from the sequences of more popular American Shorthair breed, which is related to more breeds than the Abyssinian cat. By combining advanced genomics technologies, including PacBio long-read sequencing and Hi-C- and optical mapping data-based sequence scaffolding, we compared AnAms1.0 to existing Felidae genome assemblies (20 scaffolds, scaffolds N50&#xa0;>&#xa0;150 Mbp). Homology-based and ab initio gene annotation through Iso-Seq and RNA-Seq was used to identify new coding genes and splice variants. RESULTS: AnAms1.0 demonstrated superior contiguity and accuracy than existing Felidae genome assemblies. Using AnAms1.0, we identified over 1.5 thousand structural variants and 29 million repetitions compared to felCat9. Additionally, we identified > 1,600 novel protein-coding genes. Notably, olfactory receptor structural variants and cardiomyopathy-related variants were identified. CONCLUSION: AnAms1.0 facilitates the discovery of novel genes related to normal and disease phenotypes in domestic cats. The analyzed data are publicly accessible on Cats-I (https://cat.annotation.jp/), which we established as a platform for accumulating and sharing genomic resources to discover novel genetic traits and advance veterinary medicine.

Animals

Assembly and comparative analysis of the mitochondrial genome of Pleione yunnanensis: genome structure and evolutionary insights.

BACKGROUND: Pleione yunnanensis a terrestrial or semi-epiphytic herbaceous plant belonging to the Orchidaceae family, is valued for both its medicinal uses and ornamental appeal. Although its chloroplast genomes have been sequenced, its complete mt genome had not previously been resolved, limiting genetic and evolutionary studies of the species. RESULTS: In this work, we assembled and characterized the first complete mt genome of P. yunnanensis, revealing a structurally complex, multibranched system composed of 14 circular-mapping molecules totaling 468,176&#xa0;bp with a GC content of 44.32%. The genome encodes 44 annotated genes, including 28 protein-coding genes (PCGs), 15 tRNAs, and one rRNA. The multibranched architecture provides new evidence supporting the dynamic and recombinational nature of plant mt genomes. Repeat analysis uncovered 29 simple sequence repeats (SSRs), 19 tandem repeats, and 118 dispersed repeats, indicating a comparatively lower repeat abundance than that found in closely related orchids with similar mt genome sizes. Codon-usage profiling of PCGs showed a marked bias toward A/T-ending codons. Prediction of RNA editing sites identified 4,708 putative edits across mitochondrial PCGs. Most mitochondrial genes displayed Ka/Ks ratios close to 1.0, suggesting relaxed selective constraints or lineage-specific evolutionary patterns rather than strong positive selection. Moreover, we detected 69 chloroplast-derived homologous fragments, including 15 intact genes, suggesting ongoing plastid-mitochondrial DNA transfer. Phylogenetic reconstruction and collinearity comparisons demonstrated that P. yunnanensis clustered closely with Dendrobium species, including D. amplum and D. hancockii, within the Orchidaceae clade. CONCLUSIONS: This study provides the first complete mt genome of P. yunnanensis, providing a foundational genomic resource for the genus Pleione. The results not only improve our understanding of mt genome structure and evolution in Orchidaceae, but also offer valuable molecular evidence for phylogenetic inference, germplasm identification, and conservation of this endangered medicinal species.

Orchidaceae

SynFlow: an interactive online genome structural variant viewer.

MOTIVATION: Structural variations (SVs), including inversions, translocations (TRAs), duplications, and large insertions or deletions, are key drivers of genome evolution and phenotypic diversity. With the increasing number of high-quality, chromosome-scale genome assemblies, the ability to detect and interpret SVs has become a crucial aspect of modern genomics. While SV detection has advanced, most visualization methods produce static plots that fall short when researchers, particularly in comparative genomics, need to interactively explore large datasets, zoom into specific genomic regions, or dynamically filter structural events in real time. RESULTS: To address this gap, we introduce SynFlow, a lightweight, web-based interactive application specifically designed for exploring and visualizing SVs identified by SyRI. We demonstrate that SynFlow can reproduce complex static synteny plots published in literature, but transforms them into dynamic, shareable visualizations that support real-time filtering, reordering, and deep exploration of specific SVs, including TRAs. SynFlow is available as a web server and offers multiple entry points: browsing precomputed datasets (e.g. banana and grapevine genomes), uploading user-provided SyRI outputs, or running an integrated workflow to produce and visualize SVs on the fly. AVAILABILITY AND IMPLEMENTATION: https://synflow.southgreen.fr; source code https://github.com/SouthGreenPlatform/synflow; preprocessing Snakemake workflow https://gitlab.cirad.fr/agap/cluster/snakemake/synflow.

Software