BOL: Related items

truvari: Structural variant comparison tool for VCFs

Jit — Tue, 30 Jun 2020 21:30:44 -0500

Structural variant comparison tool for VCFs

Given benchmark and comparsion sets of SVs, calculate the recall, precision, and f-measure.

Spiral Genetics

Motivation

Address of the bookmark: https://github.com/spiralgenetics/truvari

Clustergrammer is a web-based tool for visualizing high-dimensional data as an interactive and shareable hierarchically clustered heatmap

BioStar — Sun, 23 Aug 2020 19:30:17 -0500

Clustergrammer is a web-based tool for visualizing high-dimensional data (e.g. a matrix) as an interactive and shareable hierarchically clustered heatmap. Clustergrammer's front end (Clustergrammer-JS) is built using D3.js and its back-end (Clustergrammer-PY) is built using Python. Clustergrammer produces highly interactive visualizations that enable intuitive exploration of high-dimensional data and has several biology-specific features (e.g. enrichment analysis, see Biology-Specific Features) to facilitate the exploration of gene-level biological data.

Address of the bookmark: https://github.com/MaayanLab/clustergrammer

JumboDB: tool for de Bruijn graph construction

BioStar — Tue, 17 Aug 2021 13:33:46 -0500

jumboDB tool for fast de Bruijn graph construction from long sequences (reads or genomes) with very low error rate. JumboDB is not a genome assembler by itself but rather a subroutine that translates a set of reads into compressed de Bruijn graph.

More at https://github.com/AntonBankevich/jumboDB

Address of the bookmark: https://github.com/AntonBankevich/jumboDB

bacLIFE: an automated genome mining tool for identification of lifestyle associated genes

BioStar — Fri, 15 Mar 2024 04:59:14 -0500

bacLIFE is a streamlined computational workflow that annotates bacterial genomes and performs large-scale comparative genomics to predict bacterial lifestyles and to pinpoint candidate genes, denominated lifestyle-associated genes (LAGs), and biosynthetic gene clusters associated with each lifestyle detected. This whole process is divided into different modules:

Clustering module Predicts, clusters and annotates the genes of every input genome
Lifestyle prediction Employs a machine learning model to forecast bacterial lifestyle or other specified metadata
Analitical module (Shiny app) Results from the previous modules are embedded in a user-friendly interface for comprehensive and interactive comparative genomics.

You can find the complete wiki here [https://github.com/Carrion-lab/bacLIFE/wiki/bacLIFE-wiki]

Address of the bookmark: https://github.com/Carrion-lab/bacLIFE

NGenomeSyn: an easy-to-use and flexible tool for publication-ready visualization of syntenic relationships across multiple genomes

LEGE — Tue, 10 Sep 2024 04:54:55 -0500

NGenomeSyn: an easy-to-use and flexible tool for publication-ready visualization of syntenic relationships across multiple genomes

NGenomeSyn [multiple (N) Genome Synteny], for publication-ready visualization of syntenic relationships of the whole genome or local region and genomic features (e.g. repeats, structural variations, genes) across multiple genomes with a high customization. NGenomeSyn provides an easy way for its users to visualize a large amount of data with a rich layout by simply adjusting options for moving, scaling, and rotation of target genomes. Moreover, NGenomeSyn could be applied on the visualization of relationships on non-genomic data with similar input formats.

https://academic.oup.com/bioinformatics/article/39/3/btad121/7072460

Address of the bookmark: https://github.com/hewm2008/NGenomeSyn

Artificial intelligence is more accurate than doctors in diagnosing breast cancer

BioStar — Wed, 01 Jan 2020 22:12:34 -0600

Artificial intelligence is more accurate than doctors in diagnosing breast cancer from mammograms, a study in the journal Nature suggests.

An international team, including researchers from Google Health and Imperial College London, designed and trained a computer model on X-ray images from nearly 29,000 women.

The algorithm outperformed six radiologists in reading mammograms.

AI was still as good as two doctors working together.

Unlike humans, AI is tireless. Experts say it could improve detection. Read More: https://www.bbc.com/news/health-50857759

HiCanu: accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads

BioStar — Fri, 27 Mar 2020 22:49:31 -0500

HiCanu, a significant modification of the Canu assembler designed to leverage the full potential of HiFi reads via homopolymer compression, overlap-based error correction, and aggressive false overlap filtering.

More at https://www.biorxiv.org/content/10.1101/2020.03.14.992248v3

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

Hifiasm: a haplotype-resolved assembler for accurate Hifi reads

Jit — Thu, 24 Dec 2020 10:03:36 -0600

Hifiasm is a fast haplotype-resolved de novo assembler for PacBio Hifi reads. It can assemble a human genome in several hours and works with the California redwood genome, one of the most complex genomes sequenced so far. Hifiasm can produce primary/alternate assemblies of quality competitive with the best assemblers. It also introduces a new graph binning algorithm and achieves the best haplotype-resolved assembly given trio data.

Address of the bookmark: https://github.com/chhylp123/hifiasm

dna2bit: an ultra-fast and accurate genomic distance estimation software

LEGE — Sun, 31 Aug 2025 06:24:58 -0500

dna2bit is a software tool developed in C++11, leveraging the capabilities of OpenMP for parallel computing and the popcount technique for efficient bit manipulation. It has been thoroughly tested using the g++ and clang compilers on both Linux and MacOS platforms.

Address of the bookmark: https://github.com/lijuzeng/dna2bit

RapClust: Accurate, Lightweight Clustering of de novo Transcriptomes using Fragment Equivalence Classes

Rahul Nayak — Thu, 04 Oct 2018 17:57:10 -0500

RapClust is a tool for clustering contigs from de novo transcriptome assemblies. RapClust is designed to be run downstream of the Sailfish or Salmon tools for rapid transcript-level quantification. Specifically, RapClust relies on the fragment equivalence classes computed by these tools in order to determine how seqeunce is shared across the transcriptome, and how reads map to potentially-related contigs across different conditions.

Address of the bookmark: https://github.com/COMBINE-lab/RapClust