BOL: Related items

mutatrix: a population genome simulator which generates simulated genomes.

Jit — Tue, 28 Jan 2020 04:06:58 -0600

genome simulation across a population with zeta-distributed allele frequency, snps, insertions, deletions, and multi-nucleotide polymorphisms

More at https://github.com/ekg/mutatrix

./mutatrix -S sample -P test/ -p 2 -n 10 reference.fasta

Address of the bookmark: https://github.com/ekg/mutatrix

shinyChromosome:a GUI for the interactive creation of non-circular whole genome diagrams

Jit — Sat, 29 Feb 2020 00:39:50 -0600

shinyChromosome is a graphical user interface for interactive creation of non-circular whole genome diagrams developed using the R Shiny package.

To create single-genome plot by aligning genome data along all chromosomes of a single genome, go to the Single-genome plot menu.

To cretae two-genome plot for comparison of data across two genomes, go to the Two-genome plot menu.

For the detail format of input data, check the Input data format submenu of the Help menu.

shinyChromosome is deployed at http://150.109.59.144:3838/shinyChromosome/, http://shinyChromosome.ncpgr.cn, and https://yimingyu.shinyapps.io/shinyChromosome for online use. The source code and manual of shinyChromosome are freely available at https://github.com/venyao/shinyChromosome.

https://yimingyu.shinyapps.io/shinychromosome/

https://www.sciencedirect.com/science/article/pii/S1672022919301883

Address of the bookmark: https://yimingyu.shinyapps.io/shinychromosome/

merqury: Evaluate genome assemblies with k-mers

Jit — Fri, 03 Jul 2020 19:29:34 -0500

Often, genome assembly projects have illumina whole genome sequencing reads available for the assembled individual. The k-mer spectrum of this read set can be used for independently evaluating assembly quality without the need of a high quality reference. Merqury provides a set of tools for this purpose.

More at https://www.biorxiv.org/content/10.1101/2020.03.15.992941v1.full

Address of the bookmark: https://github.com/marbl/merqury

Flanker

Rahul Nayak — Sat, 27 Feb 2021 22:04:53 -0600

Flanker, a Python package which performs alignment-free clustering of gene flanking sequences in a consistent format, allowing investigation of mobile genetic elements (MGEs) without prior knowledge of their structure. Flanker can be flexibly parameterised to finetune outputs by characterising upstream and downstream regions separately and investigating variable lengths of flanking sequence.

Address of the bookmark: https://github.com/wtmatlock/flanker

Understanding kmer !

BioStar — Wed, 18 Aug 2021 04:27:51 -0500

What is a k-mer anyway? A k-mer is just a sequence of k characters in a string (or nucleotides in a DNA sequence). Now, it is important to remember that to get all k-mers from a sequence you need to get the first k characters, then move just a single character for the start of the next k-mer and so on. Effectively, this will create sequences that overlap in k-1 positions.

Address of the bookmark: https://bioinfologics.github.io/post/2018/09/17/k-mer-counting-part-i-introduction/

ncbi-datasets-cli -- Quickstart: command line tools !

Jit — Tue, 07 Dec 2021 02:51:26 -0600

Install and use the NCBI Datasets command line tools

The NCBI Datasets datasets command line tools are datasets and dataformat .

Use datasets to download biological sequence data across all domains of life from NCBI.

Use dataformat to convert metadata from JSON Lines format to other formats.

Conda download:

https://anaconda.org/conda-forge/ncbi-datasets-cli

Buld Download

https://www.ncbi.nlm.nih.gov/datasets/builder/?tax_id=29979

Address of the bookmark: https://www.ncbi.nlm.nih.gov/datasets/docs/v1/quickstarts/command-line-tools/

Smudgeplot: Inference of ploidy and heterozygosity structure using whole genome sequencing data

Neel — Fri, 25 Feb 2022 04:42:09 -0600

This tool extracts heterozygous kmer pairs from kmer count databases and performs gymnastics with them. We are able to disentangle genome structure by comparing the sum of kmer pair coverages (CovA + CovB) to their relative coverage (CovB / (CovA + CovB)). Such an approach also allows us to analyze obscure genomes with duplications, various ploidy levels, etc.

Smudgeplots are computed from raw or even better from trimmed reads and show the haplotype structure using heterozygous kmer pairs. For example:

Address of the bookmark: https://github.com/KamilSJaron/smudgeplot

GenomeQC: a quality assessment tool for genome assemblies and gene structure annotations

Neel — Thu, 19 May 2022 04:29:05 -0500

The GenomeQC web application is implemented in R/Shiny version 1.5.9 and Python 3.6 and is freely available at https://genomeqc.maizegdb.org/ under the GPL license. All source code and a containerized version of the GenomeQC pipeline is available in the GitHub repository https://github.com/HuffordLab/GenomeQC.

https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-020-6568-2

Address of the bookmark: https://github.com/HuffordLab/GenomeQC

PhyloHerb: A high‐throughput phylogenomic pipeline for processing genome skimming data

Abhi — Wed, 06 Sep 2023 00:14:28 -0500

Phylogenomic Analysis Pipeline for Herbarium Specimens

What is PhyloHerb: PhyloHerb is a wrapper program to process genome skimming data collected from plant materials. The outcomes include the plastid genome (plastome) assemblies, mitochondrial genome assemblies, nuclear ribosomal DNAs (NTS+ETS+18S+ITS1+5.8S+ITS2+28S), alignments of gene and intergenic regions, and a species tree. It is designed to be a high throughput program dealing with lower quality data. Examples include low-coverage (5x cpDNA) plastome phylogeny, recycling plastid genes from target enrichment data, retrieving low-copy nuclear genes from medium coverage (5x nucDNA) genome skimming.

License: GNU General Public License

Citation:

Cai, Liming, Hongrui Zhang, and Charles C. Davis. 2022. PhyloHerb: A high‐throughput phylogenomic pipeline for processing genome‐skimming data. Applications in Plant Sciences 10(3): 1–9. https://doi.org/10.1002/aps3.11475

Address of the bookmark: https://github.com/lmcai/PhyloHerb/

The Day We Began Reading the DNA of the World

Jitendra Narayan — Sat, 05 Sep 2026 01:43:21 -0500

Picture waking up and knowing that in one lab, a scientist is reading the DNA of a whale. In another, a team is sequencing a rare plant. Meanwhile, researchers in India are decoding the genomes of different human populations.

Many organisms. Many countries. All share one remarkable goal: to understand the genetic story of life.

DNA is nature's instruction manual, written with just four letters: A, T, C, and G. For years, scientists could only read small sections of this huge book. Now, new sequencing technology lets us read entire genomes like never before.

One of the most ambitious projects is the Earth BioGenome Project (EBP). Its goal is to create reference genomes for about 1.5 million known eukaryotic species. This project links genome research across continents, species, and scientific fields.

But this story goes beyond just animals and plants.

A New Chapter in Human Genomics

Large human genome projects are changing how we understand our own genetic diversity.

India's GenomeIndia project has sequenced thousands of people from different populations. This work is uncovering genetic variation that global databases have often missed.

Similar population-scale effSimilar large-scale projects are happening worldwide. The All of Us Research Program in the United States, Europe's 1+ Million Genomes initiative, South Korea's national genomic data program, and projects in Saudi Arabia, Australia, and Singapore are all building huge genomic resources.collect DNA.

The real goal is to link genomes with health, disease, and other biological information. This creates a base for more accurate research and, in time, more personalized medicine.

A Race Against Time

There is also an important twist.

We are sequencing Earth's biodiversity even as many species face growing environmental threats.

A genome alone cannot save a species, but it does keep important information about its biology, evolution, and genetic diversity. This knowledge helps scientists understand risks, guide conservation, and find traits that could help agriculture or medicine.

Projects like the Darwin Tree of Life, which studies species in Britain and Ireland, and the African BioGenome Project, which is growing genomics work across Africa, are key parts of this worldwide effort.

Projects to Watch

Earth BioGenome Project (EBP) - A global effort to sequence and annotate roughly 1.5 million known eukaryotic species and create a comprehensive reference library of Earth's biodiversity.
Vertebrate Genomes Project (VGP) - Focuses on producing high-quality reference genomes for vertebrate species, providing a major foundation for the wider Tree of Life.
Darwin Tree of Life - A UK and Ireland initiative aiming to sequence approximately 70,000 species, creating a detailed genomic map of regional biodiversity.
African BioGenome Project (AfricaBP) - A pan-African initiative focused on sequencing Africa's biodiversity while strengthening genomics and bioinformatics capacity across the continent.
European Reference Genome Atlas (ERGA) - A European effort to generate high-quality reference genomes for Europe's biodiversity and connect national sequencing efforts.
Canada BioGenome Project - Building reference genomes for Canadian biodiversity, supporting conservation, research and the study of ecosystems.
California Conservation Genomics Project - Uses genomics to understand and protect California's biodiversity and help inform conservation decisions.
Bat1K - An ambitious global effort to sequence the genomes of all known bat species, helping scientists study their evolution, longevity, immunity and unique biology.
Bird 10,000 (B10K) - A global project aiming to create genome resources covering the world's bird diversity and reconstruct avian evolutionary history.
Global Invertebrate Genomics Alliance (GIGA) - Builds genomic resources for the enormous and genetically diverse world of invertebrates.
GenomeIndia - India's national human-genome initiative, designed to capture the country's extraordinary population diversity and create a reference resource for Indian genomics.
All of Us Research Program - A US national research program combining genomic information with health and lifestyle data at population scale.
1+ Million Genomes / Genome of Europe - A European effort to enable secure, cross-border use of genomic and health data and develop genome-scale resources involving more than one million people.
Korea National Integrated Bio Big Data Project - South Korea's large-scale national effort combining genomic and health information from a very large population cohort.
Saudi Genome Program - A national genomics initiative focused on genetic diseases, population genomics and precision medicine in Saudi Arabia.
Australian Genomics / Genomics Health Futures Mission - Australia's growing investment in genomic medicine, rare disease research and population-scale health genomics.

The Library of Life

The fuThe future of genomics is not just about sequencing one genome at a time. Now, it is about creating a worldwide network of genomes—human and non-human, individual and species—linked by powerful databases and advanced computational tools.ine a library without shelves.

In this library, the books are genomes. The pages are made of DNA. Scientists and machines are the readers. And this library is still being written. Each genome sequenced today adds a new page to the story of life and helps us better understand our place in it.