<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/44902?offset=200 https://bioinformaticsonline.com/bookmarks/view/43690/ucsc-sars-cov-2-genome-browser Thu, 06 Jan 2022 06:48:40 -0600 https://bioinformaticsonline.com/bookmarks/view/43690/ucsc-sars-cov-2-genome-browser <![CDATA[UCSC SARS-CoV-2 Genome Browser]]> The UCSC SARS-CoV-2 Genome Browser (https://genome.ucsc.edu/covid19.html) is an adaptation of our popular genome-browser visualization tool for this virus, containing many annotation tracks and new features, including conservation with similar viruses, immune epitopes, RT–PCR and sequencing primers and CRISPR guides. We invite all investigators to contribute to this resource to accelerate research and development activities globally.

Address of the bookmark: https://www.nature.com/articles/s41588-020-0700-8

]]> Jit https://bioinformaticsonline.com/bookmarks/view/43859/mumco-is-a-simple-bash-script-that-uses-whole-genome-alignment-information-provided-by-mummer-v4-to-detect-variants Wed, 27 Apr 2022 04:34:12 -0500 https://bioinformaticsonline.com/bookmarks/view/43859/mumco-is-a-simple-bash-script-that-uses-whole-genome-alignment-information-provided-by-mummer-v4-to-detect-variants <![CDATA[MUM&Co is a simple bash script that uses Whole Genome Alignment information provided by MUMmer (v4) to detect variants.]]> MUM&Co is able to detect:
Deletions, insertions, tandem duplications and tandem contractions (>=50bp & <=150kb)
Inversions (>=1kb) and translocations (>=10kb)

Address of the bookmark: https://github.com/SAMtoBAM/MUMandCo

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/44537/the-atcc-genome-portal Wed, 15 May 2024 14:24:16 -0500 https://bioinformaticsonline.com/bookmarks/view/44537/the-atcc-genome-portal <![CDATA[The ATCC Genome Portal]]> The ATCC Genome Portal (AGP, https://genomes.atcc.org/) is a database of authenticated genomes for bacteria, fungi, protists, and viruses held in ATCC’s biorepository. It now includes 3,938 assemblies (253% increase) produced under ISO 9000 by ATCC. Here, we present new features and content added to the AGP for the research community.

Address of the bookmark: https://genomes.atcc.org/

]]> Abhi https://bioinformaticsonline.com/bookmarks/view/44489/proksee Wed, 27 Mar 2024 11:11:54 -0500 https://bioinformaticsonline.com/bookmarks/view/44489/proksee <![CDATA[Proksee]]> 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
Nucleic Acids Research, 2023, gkad326, https://doi.org/10.1093/nar/gkad326

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

]]> LEGE https://bioinformaticsonline.com/bookmarks/view/44628/uncovar-workflow-for-transparent-and-robust-virus-variant-calling-genome-reconstruction-and-lineage-assignment Mon, 05 Aug 2024 23:01:29 -0500 https://bioinformaticsonline.com/bookmarks/view/44628/uncovar-workflow-for-transparent-and-robust-virus-variant-calling-genome-reconstruction-and-lineage-assignment <![CDATA[UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment]]> 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/

]]> BioStar https://bioinformaticsonline.com/blog/view/44754/early-genome-screening-the-new-health-horoscope Thu, 02 Jan 2025 19:44:36 -0600 https://bioinformaticsonline.com/blog/view/44754/early-genome-screening-the-new-health-horoscope <![CDATA[Early Genome Screening: The New Health Horoscope!]]> 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:

  1. Accuracy and Interpretation: Genetic predisposition does not guarantee disease. Misinterpretation of results can lead to unnecessary anxiety or unwarranted medical interventions.

  2. Privacy and Data Security: Genetic data is highly sensitive. Ensuring robust data protection measures is crucial to prevent misuse.

  3. 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.

 

]]> LEGE https://bioinformaticsonline.com/bookmarks/view/40351/repeatmodeler2-automated-genomic-discovery-of-transposable-element-families Mon, 02 Dec 2019 06:52:29 -0600 https://bioinformaticsonline.com/bookmarks/view/40351/repeatmodeler2-automated-genomic-discovery-of-transposable-element-families <![CDATA[RepeatModeler2: automated genomic discovery of transposable element families]]> RepeatModeler2 represents a valuable addition to the genome annotation toolkit that will enhance the identification and study of TEs in eukaryotic genome sequences. RepeatModeler2 is available as source code or a containerized package under an open license (https://github.com/Dfam-consortium/RepeatModeler, https://github.com/Dfam-consortium/TETools).

Address of the bookmark: https://github.com/Dfam-consortium/TETools

]]> Neel https://bioinformaticsonline.com/bookmarks/view/34445/inc-seq-accurate-single-molecule-reads-using-nanopore-sequencing Mon, 27 Nov 2017 10:38:56 -0600 https://bioinformaticsonline.com/bookmarks/view/34445/inc-seq-accurate-single-molecule-reads-using-nanopore-sequencing <![CDATA[INC-Seq: accurate single molecule reads using nanopore sequencing]]> INC-Seq reads enabled accurate species-level classification, identification of species at 0.1 % abundance and robust quantification of relative abundances, providing a cheap and effective approach for pathogen detection and microbiome profiling on the MinION system.

Address of the bookmark: https://github.com/CSB5/INC-Seq

]]> Jit https://bioinformaticsonline.com/bookmarks/view/39689/msaprobs-parallel-and-accurate-multiple-sequence-alignment Tue, 09 Jul 2019 23:58:44 -0500 https://bioinformaticsonline.com/bookmarks/view/39689/msaprobs-parallel-and-accurate-multiple-sequence-alignment <![CDATA[MSAProbs - Parallel and accurate multiple sequence alignment]]> MSAProbs is a well-established state-of-the-art multiple sequence alignment algorithm for protein sequences. The design of MSAProbs is based on a combination of pair hidden Markov models and partition functions to calculate posterior probabilities. Assessed using the popular benchmarks: BAliBASE, PREFAB, SABmark and OXBENCH, MSAProbs achieves statistically significant accuracy improvements over the existing top performing aligners, including ClustalW, MAFFT, MUSCLE, ProbCons and Probalign. In addition, MSAProbs is optimized for shared-memory CPUs by employing a multi-threaded design, and further parallelized for distributed-memory systems using MPI to overcome high memory overhead barrier and achieve good parallel and data-size scalability.

Address of the bookmark: http://msaprobs.sourceforge.net/homepage.htm#latest

]]> Neel https://bioinformaticsonline.com/bookmarks/view/42413/liftoff-an-accurate-gff3gtf-lift-over-pipeline Sun, 20 Dec 2020 01:36:37 -0600 https://bioinformaticsonline.com/bookmarks/view/42413/liftoff-an-accurate-gff3gtf-lift-over-pipeline <![CDATA[Liftoff: An accurate GFF3/GTF lift over pipeline]]> Liftoff is a tool that accurately maps annotations in GFF or GTF between assemblies of the same, or closely-related species. Unlike current coordinate lift-over tools which require a pre-generated “chain” file as input, Liftoff is a standalone tool that takes two genome assemblies and a reference annotation as input and outputs an annotation of the target genome.

Address of the bookmark: https://github.com/agshumate/Liftoff

]]> Neel