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At least 19 recordsLinked to original sources

PubMed2026

Diagnostic utility of fasting versus non-fasting blood glucose: contextualising testing strategies-a narrative review.

Diabetes mellitus is a chronic metabolic disorder characterised by impaired glucose homeostasis, resulting in persistent hyperglycaemia. Accurate and prompt diagnosis is essential for early intervention and prevention of long-term complications. Fasting blood glucose levels have traditionally been central to the diagnosis and monitoring of diabetes mellitus. However, growing evidence highlights the clinical relevance of non-fasting glucose measures, including postprandial glucose, random plasma glucose, and glycated haemoglobin (HbA1c) levels. Practical challenges, safety concerns, and evolving insights into glucose physiology have prompted renewed interest in flexible and context-driven approaches to glucose testing. This narrative review examines the physiological basis of fasting and non-fasting glucose regulation and critically evaluates their roles in diabetes screening, diagnosis, and monitoring. It also discusses the strengths and limitations of measuring fasting blood glucose, oral glucose tolerance, HbA1c, random plasma glucose, postprandial glucose, and continuous glucose monitoring. Special attention is given to pre-analytical and practical considerations, patient safety, and the ability of non-fasting measures to capture early metabolic dysfunction and real-world glycaemic exposure. This article reviews evidence supporting the prognostic value of postprandial hyperglycaemia and the expanding role of non-fasting monitoring tools. Non-fasting glucose testing offers substantial advantages in terms of accessibility, safety, and clinical relevance, and is well-suited for population screening and routine diabetes monitoring. Fasting glucose testing remains essential for specific diagnostic and research applications, particularly when strict metabolic standardisation is required. A context-driven framework that prioritises non-fasting approaches while reserving fasting tests for targeted indications provides a balanced and patient-centred strategy for contemporary diabetes care.

Diabetes screening↗

PubMed2025

PseudotimeDE-fast: fast testing of differential gene expression along cell pseudotime.

SUMMARY: Identifying differentially expressed (DE) genes along cell pseudotime is crucial for understanding dynamic biological processes captured by single-cell RNA sequencing. However, existing DE methods either produce invalid P-values by ignoring the uncertainty in pseudotime inference or struggle to scale with the growing size of modern datasets. To address these limitations, we introduce PseudotimeDE-fast, a scalable method for detecting DE genes along pseudotime with well-calibrated P-values. Through comprehensive simulations and real-data analyses, we demonstrate that PseudotimeDE-fast delivers comparable or superior performance to existing approaches while offering substantial improvements in computational efficiency. AVAILABILITY AND IMPLEMENTATION: PseudotimeDE-fast is implemented in R with Rcpp acceleration and released under the MIT license. The source code is available at: https://github.com/dsong-lab/PseudotimeDE.

Single-Cell Analysis↗

PubMed2026

Pharmacokinetic Differences Between Fast-Acting, Standard, and Placebo Cannabis Edibles.

INTRODUCTION: Edibles have become the second-most used cannabis product in legal U.S. states, wherein 64% of cannabis consumers reported using edibles within the past year. Among expansions to the legal cannabis industry are the newly marketed "fast-acting" edible compounds, which may address many of the issues associated with edible use related to overdose and dose management. The study hypotheses were that fast-acting edibles would reach peak concentration significantly faster than standard edibles and placebo edibles. MATERIALS AND METHODS: Twenty participants completed three arms within-subjects designed study to test hypotheses. The three arms were ingestion of a (1) fast-acting edible, (2) a standard edible, and (3) a Δ9-tetrahydrocannabinol (THC) terpene-derived placebo edible that was indistinguishable from the two THC-containing edibles. Blood plasma was analyzed for the presence of THC and THC analytes. The pharmacokinetic parameters tested were time to max concentration (Tmax), maximum concentration (Cmax), terminal half-life (t1/2), and area under the curve (AUC). RESULTS: Results supported study hypotheses in that Tmax was significantly faster for the fast-acting edible, observed 30 min post-ingestion and, on average, 30 min earlier than the Tmax for the standard edible. There were no significant differences between the fast-acting and standard edibles on Cmax, t1/2, and AUC; however, both the fast-acting and standard edibles were significantly different compared with the placebo across all pharmacokinetic parameters. DISCUSSION: The results indicate that the microencapsulation technology used to create the fast-acting edible enabled analyte concentrations to peak significantly faster compared to the standard and placebo edibles.

Humans↗

PubMed2026

Transcriptomic changes in the gut mucosa of fasting northern elephant seal pups reveal immune modulation during early microbiome establishment.

Fasting is an integral component of the life-history of many species. Following abrupt weaning, northern elephant seal pups (Mirounga angustirostris) undergo an extended post-weaning fast of approximately 60 days. During this period, enteric bacterial diversity increases, suggesting that host immune regulation may facilitate the establishment of microbial communities. However, the molecular processes occurring within the intestinal mucosa during this transition remain poorly understood. To investigate these mechanisms, we characterized transcriptional changes in the enteric mucosa of male and female northern elephant seal pups sampled at weaning and after one month of fasting. Total RNA isolated from rectal swabs was sequenced and aligned to the Mirounga angustirostris reference genome. Differential gene expression and gene set enrichment analyses were used to identify genes and pathways associated with fasting and sex-specific responses. Fasting was accompanied primarily by transcriptional downregulation, including genes involved in antimicrobial defense, inflammation, protein turnover, and epithelial remodeling. In contrast, several genes associated with B-cell activity and immune recognition were upregulated. Gene Set Enrichment Analysis revealed coordinated activation of immune-regulatory pathways indicating dynamic modulation of intestinal immunity rather than generalized immune suppression. Pronounced sex-specific differences were also observed. Male pups exhibited transcriptional patterns consistent with enhanced immune tolerance, whereas females showed broader immune-pathway activation, including enrichment of pro-inflammatory and stress-response pathways. Several non-coding RNAs also displayed sex-specific changes in expression. Together, these findings suggest that fasting induces transcriptional remodeling of the gut and may contribute to immune regulation during a critical period of microbiome establishment in northern elephant seal pups.

Animals↗

PubMed2026

Fasting-refeeding regimes induce compensatory growth and muscle transcriptomic remodeling in juvenile Qihe gibel carp (Carassius gibelio var. Qihe).

Compensatory growth, an important adaptive response in fish, holds considerable potential for improving feeding efficiency in aquaculture. To identify an optimal fasting-refeeding strategy for juvenile Qihe gibel carp (Carassius gibelio var. Qihe) and to clarify the mechanisms underlying the compensatory growth, we divided two-month-old fish into four groups, namely S0 group (continuous feeding for 28 days), S2 group (4 cycles of 2-day fasting followed by 5-day refeeding), S4 group (fasting for 4 days followed by refeeding for 24 days), and S8 group (fasting for 8 days followed by refeeding for 20 days), then growth performance, muscle tissue morphology, biochemical responses, and muscle transcriptomic profiles under different feeding regimes were investigated. After a 28-day aquaculture experiment, fish in the S4 group exhibited significantly greater body length and weight than those in the S0, S2, and S8 groups, indicating over-compensatory growth. Histological analysis further showed that muscle growth in the S4 group was mainly associated with myofiber hyperplasia. Different feeding regimes also induced distinct changes in hepatic antioxidant and metabolic enzyme activities, as well as intestinal digestive enzyme activities. Transcriptome analysis revealed that the forkhead box O (FoxO) signaling pathway was significantly enriched during compensatory growth. Key genes, including serum/glucocorticoid regulated kinase 1 (sgk1) and insulin receptor substrate 1 (irs1), were predicted to play important roles in this process. Overall, these results indicate that fasting for 4 days followed by refeeding for 24 days (the S4 regime) is the optimal strategy for inducing compensatory growth in juvenile Qihe gibel carp. This study provides new insights into the morphological, physiological, and molecular basis of compensatory growth and offers a scientific foundation for developing efficient and sustainable feeding strategies for this species.

Animals↗

PubMed2026

A combined stimulus of acute fasting and exercise modulates hippocampal mitochondrial quality control in healthy mice.

BACKGROUND AND AIMS: Exercise and fasting are recognized for their ability to improve brain health and mitigate neurodegeneration. However, little is known about how these interventions acutely impact mitochondrial quality control mechanisms including mitophagy. METHODS: We examined the effects of a single bout of fasting and exercise (FEx) on hippocampal mitochondrial function and proteomic remodeling in male and female mice. To assess in vivo autophagy dynamics, we combined proteomics with chloroquine (CQ) inhibition of autophagic flux. Mice were assigned to sedentary (Sed), fasting (F), exercise (Ex), or combined FEx groups and received unilateral intrahippocampal injections of CQ or PBS following treatments. Four hours later, hippocampi were collected for analysis. RESULTS: LC3-II levels significantly increased in the FEx group only following CQ treatment, indicating enhanced autophagic flux. Proteomic profiling showed sedentary males failed to mount a robust response to FEx however females exhibited upregulation of proteins involved in the TCA cycle, glutathione metabolism, and oxidative phosphorylation, suggesting greater mitochondrial adaptability. Functional assays supported these findings, females showed increased complex IV activity post-FEx. The mitochondrial DNA / nuclear DNA ratio increased after FEx regardless of sex, and upstream regulator analysis predicted activation of mitochondrial biogenesis. CONCLUSIONS: Together, these data reveal sex-specific mitochondrial remodeling in response to acute fasting and exercise. Defining these normative responses is critical for understanding how mitochondrial adaptability shapes resilience or vulnerability to neurological challenges.

Animals↗

PubMed2026

Nuclear class 3 PI3K co-activates fasting-specific chromatin remodelling.

Transcriptional remodelling during fasting ensures metabolic adaptation and provides health benefits across species. Although several regulators of fasting-induced transcription and chromatin are known, how nutrient levels directly influence RNA polymerase II (RNAPII) and epigenetic writers remains unclear. Here we show that lipid kinase class 3 phosphatidylinositol 3-kinase (PI3K-3), a master regulator of autophagy, also functions on chromatin as a co-activator of epigenetic writers to promote RNAPII transcription. PI3K-3 overlaps with transcriptionally engaged RNAPII phosphorylated at Ser5 and with Setd1a/COMPASS, the complex that deposits the activating H3K4me3 mark. Nuclear PI3K-3 interacts with RNAPII and Setd1a/COMPASS and promotes their chromatin binding. PI3K-3 loss reduces RNAPII-S5p and H3K4me3 at selected genes, whereas PI3K-3 overexpression co-activates p300/CBP and chromatin-targeted PI3K-3 increases H3K4me3. During starvation, PI3K-3 induces autophagy genes and drives fasted liver towards ketogenesis and lipid degradation. These findings link nutrient stress to chromatin-mediated transcriptional activation.

Chromatin Assembly and Disassembly↗

PubMed2026

MegaPX: fast and space-efficient peptide assignment method using IBF-based multi-indexing.

MOTIVATION: A central problem for metaproteomic analysis is the often-unknown taxonomic composition of the analyzed microbiomes. Using a database search, the standard approach requires prior knowledge of which proteins and taxa to include in the protein reference database or to use tailored metagenome-derived databases, which are expensive and error-prone in their generation. A possible strategy to circumvent this database search issue is de novo sequencing, where peptide sequences are directly identified from mass spectra. However, these sequences must still be mapped back to potentially extensive databases. Here, alignment-based approaches enable robust and precise results, with the potential drawback of high memory usage and long run times. RESULTS: We present MegaPX, a software for rapidly classifying de novo peptide sequences against large protein databases. MegaPX implemented as a C++-based tool, uses an alignment-free, k-mer approach as a taxonomic classification method with the possibility of generating mutated reference databases for error-tolerant searching. It uses various algorithms, including interleaved Bloom filters, to efficiently compute approximate membership queries, ensuring fast processing times while querying and indexing large databases in a multi-indexing fashion. We demonstrate the potential of MegaPX by analyzing different samples, including metaproteomics, against extensive reference databases, highlighting its use as a fast screening tool.

Software↗

PubMed2025

TIPP3 and TIPP3-fast: Improved abundance profiling in metagenomics.

We present TIPP3 and TIPP3-fast, new tools for abundance profiling in metagenomic datasets. Like its predecessor, TIPP2, the TIPP3 pipeline uses a maximum likelihood approach to place reads into labeled taxonomies using marker genes, but it achieves superior accuracy to TIPP2 by enabling the use of much larger taxonomies through improved algorithmic techniques. We show that TIPP3 is generally more accurate than leading methods for abundance profiling in two important contexts: when reads come from genomes not already in a public database (i.e., novel genomes) and when reads contain sequencing errors. We also show that TIPP3-fast has slightly lower accuracy than TIPP3, but is also generally more accurate than other leading methods and uses a small fraction of TIPP3's runtime. Additionally, we highlight the potential benefits of restricting abundance profiling methods to those reads that map to marker genes (i.e., using a filtered marker-gene based analysis), which we show typically improves accuracy. TIPP3 is freely available at https://github.com/c5shen/TIPP3.

Metagenomics↗

PubMed2026

REvolutionH-tl 2.0: A fast and robust tool for decoding evolutionary gene histories.

REvolutionH-tl is a fast, scalable, and integrated software platform for inferring orthology relationships, gene trees, species trees, and reconciled evolutionary scenarios directly from sequence data. Built upon the formal framework of best match graphs (BMGs), REvolutionH-tl predicts orthogroups and orthologous gene pairs with high accuracy, requiring neither precomputed trees nor multiple external tools. The software reconstructs event-labeled gene and species trees, seamlessly integrating reconciliation to produce fast, accurate, and biologically insightful evolutionary scenarios. Through extensive benchmarking on synthetic datasets with known ground truth, REvolutionH-tl outperforms or matches the accuracy of established tools such as OrthoFinder, Proteinortho, RAxML, GeneRax, and RANGER-DTL, while achieving significantly lower runtimes. A key innovation of REvolutionH-tl is its built-in support for detailed, publication-ready visualizations, which allow users to explore genome evolution dynamics, orthogroup composition, and reconciliation results with clarity and ease. These visual features position REvolutionH-tl as the first platform of its kind to combine analytical precision with intuitive interpretability. The software is open-source, cross-platform, and freely available at https://pypi.org/project/revolutionhtl/, providing a robust solution for large-scale evolutionary analyses in comparative genomics.

Software↗

PubMed2024

A fast comparative genome browser for diverse bacteria and archaea.

Genome sequencing has revealed an incredible diversity of bacteria and archaea, but there are no fast and convenient tools for browsing across these genomes. It is cumbersome to view the prevalence of homologs for a protein of interest, or the gene neighborhoods of those homologs, across the diversity of the prokaryotes. We developed a web-based tool, fast.genomics, that uses two strategies to support fast browsing across the diversity of prokaryotes. First, the database of genomes is split up. The main database contains one representative from each of the 6,377 genera that have a high-quality genome, and additional databases for each taxonomic order contain up to 10 representatives of each species. Second, homologs of proteins of interest are identified quickly by using accelerated searches, usually in a few seconds. Once homologs are identified, fast.genomics can quickly show their prevalence across taxa, view their neighboring genes, or compare the prevalence of two different proteins. Fast.genomics is available at https://fast.genomics.lbl.gov.

Archaea↗

PubMed2025

Heterogeneous effects of genetic variants and traits associated with fasting insulin on cardiometabolic outcomes.

Elevated fasting insulin levels (FI), indicative of altered insulin secretion and sensitivity, may precede type 2 diabetes (T2D) and cardiovascular disease onset. In this study, we group FI-associated genetic variants based on their genetic and phenotypic similarities and identify seven clusters with distinct mechanisms contributing to elevated FI levels. Clusters fall into two types: "non-diabetogenic hyperinsulinemia," where clusters are not associated with increased T2D risk, and "diabetogenic hyperinsulinemia," where T2D associations are driven by body fat distribution, liver function, circulating lipids, or inflammation. In over 1.1 million multi-ancestry individuals, we demonstrated that diabetogenic hyperinsulinemia cluster-specific polygenic scores exhibit varying risks for cardiovascular conditions, including coronary artery disease, myocardial infarction (MI), and stroke. Notably, the visceral adiposity cluster shows sex-specific effects for MI risk in males without T2D. This study underscores processes that decouple elevated FI levels from T2D and cardiovascular risk, offering new avenues for investigating process-specific pathways of disease.

Humans↗

PubMed2026

Comparative Characterization of σ32-Dependent Promoters for the Heat-Inducible Expression of FAST-PETase in Escherichia coli.

Efficient regulation of recombinant enzyme expression is an important consideration for the development of microbial biocatalysts. Heat-inducible promoters regulated by the alternative sigma factor σ32 provide an inducer-free strategy for controlling gene expression in Escherichia coli. In this study, four σ32-dependent promoters (PdnaK, PgrpE, PibpA, and PclpB) were comparatively characterized using the PET-degrading enzyme FAST-PETase fused to superfolder green fluorescent protein as a model recombinant protein. Promoter performance was evaluated based on basal leakage, induction kinetics, and expression strength following heat induction. Among the promoters examined, PdnaK exhibited the strongest heat-inducible expression and was dissected to examine the autonomous and combinatorial behavior of its promoter-derived elements. Molecular docking analysis further supported the experimental observations by showing qualitative agreement between predicted σ32-DNA interactions and promoter performance. Together, these findings provide a comparative characterization of σ32-dependent promoters and identify promoter architectures that may facilitate the development of heat-inducible recombinant enzyme expression systems in E. coli.

Escherichia coli↗

PubMed2026

Accelerating Lung Cancer Management Through Previsit Liquid Biopsy: Results From the LUNG-FAST Pilot Study.

BACKGROUND: Timely molecular profiling is essential for treatment selection in non-small cell lung cancer (NSCLC), yet delays in biomarker testing remain common. We evaluated the feasibility and early clinical impact of a nurse navigator-driven workflow to initiate liquid biopsy before the initial oncology visit. METHODS: LUNG-FAST (Liquid Biopsy for Urgent Neoplastic Genomic Profiling Focused Accelerated Stratification and Testing) was a 4-month prospective pilot at a tertiary cancer center. Intake nurse navigators identified eligible patients with suspected or newly diagnosed lung cancer and facilitated previsit liquid biopsy ordering. Feasibility, turnaround times, genomic findings, and early clinical outcomes were assessed. RESULTS: Among 64 patients, intake nurse navigators identified 94% (60/64) of eligible cases. Liquid biopsy was ordered in 58 patients, with 62% (36/58) placed before the initial oncology visit. Median turnaround time from blood draw to results was 8.5 days for commercial testing and 12.5 days for institutional testing. FDA-actionable genomic alterations were identified in 34% (22/64) of patients, while an additional 11% (7/64) harbored clinically relevant, non-FDA-actionable alterations. Overall, FDA-actionable or clinically relevant alterations were identified in 45% (29/64), with 22% detected by liquid biopsy and an additional 23% by tissue-only profiling. Median time from new patient visit to systemic therapy was 26 days. CONCLUSIONS: A nurse navigator-driven workflow enabling previsit liquid biopsy is feasible and identifies actionable genomic alterations in a substantial proportion of patients with lung cancer. Plasma and tissue profiling are complementary, and earlier plasma-based testing may expedite treatment decision-making while highlighting opportunities to optimize biomarker testing workflows.

Humans↗

PubMed2026

jsPCA: fast, scalable, and interpretable identification of spatial domains and variable genes across multi-slice and multi-sample spatial transcriptomics data.

MOTIVATION: Spatial transcriptomics technologies record genome-wide measurements of gene expression with high spatial resolution. These technologies generate large and high-dimensional datasets requiring efficient automated methods for their analysis. We introduce joint spatial PCA (jsPCA), a novel, fast, scalable and interpretable method for the automatic identification of spatial domains and variable genes in multi-slice and multi-sample spatial transcriptomics data. RESULTS: jsPCA relies on a simple mathematical formulation of a spatial covariance defined as the product of the gene expression covariance with the spatial autocorrelation. The principal components of this spatial covariance yield a biologically meaningful low-dimensional representation. From this representation, spatial domains are derived by simple clustering and spatially variable genes are identified directly from the principal component coefficients. A joint representation of multiple slices and samples without spatial alignment is obtained by computing common principal components via joint diagonalization. By leveraging data sparsity and non-convex manifold optimization, jsPCA leads to computing time in the order of seconds to minutes, substantially outperforming state-of-the-art approaches. We benchmarked jsPCA against 10 state-of-the-art methods on two reference databases. Our approach demonstrated excellent performance, comparable or better than state-of-the-art methods, while being much faster, interpretable, and scalable to very large datasets.

Journal Article↗

PubMed2025

GCfix: a fast and accurate fragment length-specific method for correcting GC bias in cell-free DNA.

MOTIVATION: Cell-free DNA (cfDNA) analysis has wide-ranging clinical applications due to its noninvasive nature. However, cfDNA fragmentomics and copy number analysis can be complicated by GC bias. There is a lack of GC correction software based on rigorous cfDNA GC bias analysis. Furthermore, there is no standardized metric for comparing GC bias correction methods across large sample sets, nor a rigorous experiment setup to demonstrate their effectiveness on cfDNA data at various coverage levels. RESULTS: We present GCfix, a method for robust GC bias correction in cfDNA data across diverse coverages. Developed following an in-depth analysis of cfDNA GC bias at the region and fragment length levels, GCfix is both fast and accurate. It works on all reference genomes and generates correction factors, tagged BAM files, and corrected coverage tracks. We also introduce two orthogonal performance metrics for (i) comparing the fragment count density distribution of GC content between expected and corrected samples, and (ii) evaluating coverage profile improvement post-correction. GCfix outperforms existing cfDNA GC bias correction methods on these metrics. AVAILABILITY AND IMPLEMENTATION: GCfix software and code for reproducing the figures are publicly accessible on GitHub: https://github.com/Rafeed-bot/GCfix_Software.

Software↗

PubMed2025

AdDeam: a fast and scalable tool for estimating and clustering reference-level damage profiles.

MOTIVATION: DNA damage patterns, such as increased frequencies of C→T and G→A substitutions at fragment ends, are widely used in ancient DNA studies to assess authenticity and detect contamination. In metagenomic studies, fragments can be mapped against multiple references or de novo assembled contigs to identify those likely to be ancient. Generating and comparing damage profiles, however, can be both tedious and time-consuming. Although tools exist for estimating damage in single reference genomes and metagenomic datasets, none efficiently cluster damage patterns. RESULTS: To address this methodological gap, we developed AdDeam, a tool that combines rapid damage estimation with clustering for streamlined analyses and easy identification of potential contaminants or outliers. Our tool takes aligned ancient DNA (aDNA) fragments from various samples or contigs as input, computes damage patterns, clusters them, and outputs representative damage profiles per cluster, a probability of each sample pertaining to a cluster, as well as a Principal Component Analysis of the damage patterns for each sample for fast visualisation. We evaluated AdDeam on both simulated and empirical datasets. AdDeam effectively distinguishes different damage levels, such as uracil-DNA glycosylase-treated samples, sample-specific damages from specimens of different time periods, and can also distinguish between contigs containing modern or ancient fragments, providing a clear framework for aDNA authentication and facilitating large-scale analyses. AVAILABILITY AND IMPLEMENTATION: AdDeam is publicly available at https://github.com/LouisPwr/AdDeam and can also be installed via Bioconda. It is implemented in Python and C++. All analysis scripts and datasets are available at https://github.com/LouisPwr/AdDeamAnalysis and on Zenodo under: 10.5281/zenodo.15052427.

Software↗

PubMed2025

polars-bio-fast, scalable, and out-of-core operations on large genomic interval datasets.

MOTIVATION: Genomic studies very often rely on computationally intensive analyses of relationships between features, which are typically represented as intervals along a 1D coordinate system (such as positions on a chromosome). In this context, the Python programming language is extensively used for manipulating and analyzing data stored in a tabular form of rows and columns, called a DataFrame. Pandas is the most widely used Python DataFrame package and has been criticized for inefficiencies and scalability issues, which its modern alternative-Polars-aims to address with a native backend written in the Rust programming language. RESULTS: polars-bio is a Python library that enables fast, parallel and out-of-core operations on large genomic interval datasets. Its main components are implemented in Rust, using the Apache DataFusion query engine and Apache Arrow for efficient data representation. It is compatible with Polars and Pandas DataFrame formats. In a real-world comparison (107 versus 1.2×106 intervals), our library runs overlap queries 6.5×, nearest queries 15.5×, count_overlaps queries 38×, and coverage queries 15× faster than Bioframe. On equally sized synthetic sets (107 versus 107), the corresponding speedups are 1.6×, 5.5×, 6×, and 6×. In streaming mode, on real and synthetic interval pairs, our implementation uses 90× and 15× less memory for overlap, 4.5× and 6.5× less for nearest, 60× and 12× less for count_overlaps, and 34× and 7× less for coverage than Bioframe. Multi-threaded benchmarks show good scalability characteristics. To the best of our knowledge, polars-bio is the most efficient single-node library for genomic interval DataFrames in Python. AVAILABILITY AND IMPLEMENTATION: polars-bio is an open-source Python package distributed under the Apache License available for major platforms, including Linux, macOS, and Windows in the PyPI registry. The online documentation is https://biodatageeks.org/polars-bio/ and the source code is available on GitHub: https://github.com/biodatageeks/polars-bio and Zenodo: https://doi.org/10.5281/zenodo.16374290. are available at Bioinformatics online.

Software↗