BOL: Related items

Proksee

LEGE — Wed, 27 Mar 2024 11:11:54 -0500

Proksee is an expert system for genome assembly, annotation and visualization. To begin using Proksee, provide a complete genome sequence, sequencing reads or a CGView/Proksee map JSON file.

Please Cite the Following

Grant JR, Enns E, Marinier E, Mandal A, Herman EK, Chen C, Graham M, Van Domselaar G, and Stothard P

Proksee: in-depth characterization and visualization of bacterial genomes

Nucleic Acids Research, 2023, gkad326, https://doi.org/10.1093/nar/gkad326

Address of the bookmark: https://proksee.ca/

UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment

BioStar — Mon, 05 Aug 2024 23:01:29 -0500

UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment

Using state of the art tools, easily extended for other viruses
Tool and database updates for critical components via Conda
Built using modern design patterns with Conda and Snakemake
Extensible and easy to customize
Submission Ready Genomes
Customizable reporting with comprehensive visualization

https://ikim-essen.github.io/uncovar/

Github https://github.com/IKIM-Essen/uncovar

Address of the bookmark: https://ikim-essen.github.io/uncovar/

Early Genome Screening: The New Health Horoscope!

LEGE — Thu, 02 Jan 2025 19:44:36 -0600

In an era where precision medicine is reshaping healthcare, genome screening is emerging as the modern equivalent of a health horoscope. It offers insights into our biological "stars," unraveling predispositions to various conditions and empowering individuals with knowledge to navigate their health journeys proactively. But how reliable is this "horoscope," and how does it impact our lives?

Understanding Genome Screening

Genome screening involves analyzing an individual's DNA to identify genetic variations that may influence health and disease susceptibility. This can range from simple single-gene tests to comprehensive whole-genome sequencing. By peering into our genetic blueprint, we can uncover risks for conditions like cancer, diabetes, cardiovascular diseases, and even rare genetic disorders.

The process is straightforward: a saliva or blood sample is collected, and advanced sequencing technologies decipher the genetic code. The results provide a personalized health map, guiding lifestyle modifications, preventive measures, or medical interventions.

A Shift from Reactive to Proactive Healthcare

Traditional healthcare often focuses on treating diseases after they manifest. Genome screening flips this model on its head, enabling a shift toward prevention and early intervention. For instance:

Cancer Risk Management: Individuals with BRCA1 or BRCA2 gene mutations can opt for enhanced screening programs or preventive surgeries to mitigate their risk of breast and ovarian cancers.
Cardiovascular Health: Genetic predispositions to conditions like familial hypercholesterolemia can prompt early cholesterol monitoring and lifestyle adjustments.
Rare Diseases: Identifying carriers of genetic disorders can aid in family planning and reduce the incidence of inherited conditions.

The Ethical and Practical Concerns

While genome screening offers incredible promise, it is not without challenges:

Accuracy and Interpretation: Genetic predisposition does not guarantee disease. Misinterpretation of results can lead to unnecessary anxiety or unwarranted medical interventions.
Privacy and Data Security: Genetic data is highly sensitive. Ensuring robust data protection measures is crucial to prevent misuse.
Accessibility and Equity: High costs and limited availability may restrict access to genome screening, exacerbating health disparities.

Balancing Science and Pseudoscience

The comparison of genome screening to horoscopes isn’t entirely unfounded. Both offer predictive insights, but the scientific foundation of genome screening distinguishes it from astrology. Unlike the alignment of celestial bodies, genetic predictions are based on rigorous data and evidence. However, the probabilistic nature of genetic predispositions underscores the importance of interpreting results in conjunction with clinical and lifestyle factors.

The Road Ahead

As genome screening becomes more affordable and integrated into routine healthcare, its potential to transform lives is immense. Policymakers, healthcare providers, and genetic counselors must collaborate to ensure ethical implementation, public awareness, and equitable access.

Imagine a future where your genetic "horoscope" is a trusted guide, not just a prediction. Early genome screening could help chart a healthier path for generations, making it a cornerstone of personalized medicine. After all, our genes might just hold the key to unlocking a future of better health and well-being.

HiTE: a fast and accurate dynamic boundary adjustment approach for full-length Transposable Elements detection and annotation in Genome Assemblies

LEGE — Sat, 20 Sep 2025 09:34:04 -0500

HiTE is a Python software that uses a dynamic boundary adjustment approach to detect and annotate full-length Transposable Elements in Genome Assemblies. In comparison to other tools, HiTE demonstrates superior performance in detecting a greater number of full-length TEs.

panHiTE

We have developed panHiTE, a comprehensive and accurate pipeline for TE detection in large-scale population genomes. It has been successfully applied to hundreds of plant population genomes, demonstrating its effectiveness and scalability.

For detailed instructions, please refer to the panHiTE tutorial.

Address of the bookmark: https://github.com/CSU-KangHu/HiTE

Krona

Jit — Wed, 22 Mar 2017 04:47:35 -0500

Krona allows hierarchical data to be explored with zooming, multi-layered pie charts. Krona charts can be created using an Excel template or KronaTools, which includes support for several bioinformatics tools and raw data formats. The interactive charts are self-contained and can be viewed with any modern web browser (see Browser support).

Address of the bookmark: https://github.com/marbl/Krona/wiki

PPanGGOLiN: Depicting microbial species diversity via a Partitioned PanGenome Graph Of Linked Neighbors

LEGE — Thu, 01 Feb 2024 00:24:32 -0600

PPanGGOLiN (Gautreau et al. 2020) is a software suite used to create and manipulate prokaryotic pangenomes from a set of either genomic DNA sequences or provided genome annotations. It is designed to scale up to tens of thousands of genomes. It has the specificity to partition the pangenome using a statistical approach rather than using fixed thresholds which gives it the ability to work with low-quality data such as Metagenomic Assembled Genomes (MAGs) or Single-cell Amplified Genomes (SAGs) thus taking advantage of large scale environmental studies and letting users study the pangenome of uncultivable species.

A complete documentation is available here.

Address of the bookmark: https://github.com/labgem/PPanGGOLiN

VG: variation graph data structures, interchange formats, alignment, genotyping, and variant calling methods

Jit — Tue, 28 Jan 2020 03:53:24 -0600

Variation graphs provide a succinct encoding of the sequences of many genomes. A variation graph (in particular as implemented in vg) is composed of:

nodes, which are labeled by sequences and ids
edges, which connect two nodes via either of their respective ends
paths, describe genomes, sequence alignments, and annotations (such as gene models and transcripts) as walks through nodes connected by edges

Address of the bookmark: https://github.com/vgteam/vg

GraphPath: A graph attention model for molecular stratification with interpretability based on the pathway-pathway interaction network

LEGE — Wed, 27 Mar 2024 20:51:21 -0500

Achieving accurate and interpretable clinical predictions requires paramount attention to thoroughly characterizing patients at both the molecular and biological pathway levels. In this paper, we present GraphPath, a biological knowledge-driven graph neural network with multi-head self-attention mechanism that implements the pathway-pathway interaction network. We train GraphPath to classify the cancer status of patients with prostate cancer based on their multi-omics profiling.

Address of the bookmark: https://github.com/amazingma/GraphPath

SATSUMA : Highly sensitive whole-genome synteny alignments.

Jit — Fri, 13 May 2016 05:25:26 -0500

Satsuma is a whole-genome synteny alignment program. It takes two genomes, computes alignments, and then keeps only the parts that are orthologous, i.e. following the conserved order and orientation of features, such as protein coding genes, non-coding genes, or neutral sequences. Satsuma does not require any pre-processing, such as repeat masking, since it will automatically detect ambiguous mappings.

Satsuma has parallelization built-in and is designed to run on multi-core architectures. The run-time for aligning two bird-size genomes (~1.2 Gb) is around two days on 24 CPUs.

You can find the manual here.
Download the latest source code from here.
Stable versions can also be downloaded from the Broad Institute's web site.

An incomplete list of questions and answers (yes, these have really been asked by our users! Please feel free to add your own by e-mailing us) is here.

If you use Satsuma in your research, please cite:
Grabherr, M. G., Russell, P., Meyer, M., Mauceli, E., Alföldi, J., Di Palma, F., & Lindblad-Toh, K. (2010). Genome-wide synteny through highly sensitive sequence alignment: Satsuma. Bioinformatics, 26(9), 1145-51.

Tutorial at http://evomics.org/learning/genomics/satsuma/

Address of the bookmark: http://satsuma.sourceforge.net/

maf2synteny

Abhimanyu Singh — Thu, 18 May 2017 05:31:30 -0500

A tool for converting for recovering synteny blocks from multiple alignment (in MAF fromat)

This tool is a standalone version of Ragout module [http://fenderglass.github./Ragout]

Address of the bookmark: https://github.com/fenderglass/maf2synteny