BOL: Related items

deepTools

Martin Jones — Sat, 08 Nov 2014 15:02:08 -0600

deepTools addresses the challenge of handling the large amounts of data that are now routinely generated from DNA sequencing centers. To do so, deepTools contains useful modules to process the mapped reads data to create coverage files in standard bedGraph and bigWig file formats. By doing so, deepTools allows the creation of normalized coverage files or the comparison between two files (for example, treatment and control). Finally, using such normalized and standardized files, multiple visualizations can be created to identify enrichments with functional annotations of the genome.

Publicaton: http://nar.oxfordjournals.org/content/early/2014/05/05/nar.gku365.full

Source Code and Wiki: https://github.com/fidelram/deepTools/wiki

Galaxy Tool Shed repository: http://toolshed.g2.bx.psu.edu/view/bgruening/deeptools

and example Galaxy workflows: http://toolshed.g2.bx.psu.edu/view/bgruening/deeptools_workflows

Entire Human Genome Sequencing !

LEGE — Tue, 02 Apr 2024 01:19:29 -0500

Cost-effective whole human genome sequencing has revolutionized the landscape of genetic research and personalized medicine by making comprehensive genetic analysis accessible to a wider population. Through advancements in sequencing technologies, such as next-generation sequencing (NGS), costs have significantly decreased, enabling researchers and healthcare providers to analyze an individual's complete genetic makeup with greater efficiency and affordability. This has profound implications for disease diagnosis, prognosis, and treatment, as it allows for the identification of genetic predispositions and the customization of healthcare interventions based on an individual's unique genetic profile. Moreover, as the cost continues to decline, the potential for population-scale genomic studies and large-scale screening programs becomes increasingly feasible, promising to further enhance our understanding of human genetics and improve healthcare outcomes on a global scale.

Here are few companies:

https://mynucleus.com/

https://myome.com/

https://nebula.org/whole-genome-sequencing-dna-test/

D-GENIES: A tool for Dotplot large Genomes in an Interactive, Efficient and Simple way

Jit — Mon, 11 Jun 2018 09:41:22 -0500

D-GENIES – for Dotplot large Genomes in an Interactive, Efficient and Simple way – is an online tool designed to compare two genomes. It supports large genome and you can interact with the dot plot to improve the visualisation. We use minimap version 2 to align the two genomes. Then, the PAF file is parsed and plotted into an interactive plot written with d3.js library. D-Genies also allows to display dot plots from other aligners by uploading their PAF or MAF alignment file. http://dgenies.toulouse.inra.fr/

Address of the bookmark: http://dgenies.toulouse.inra.fr/

SynVisio: An Interactive Multiscale Synteny Visualization Tool for McScanX.

Jit — Sun, 31 May 2020 02:01:14 -0500

SynVisio lets you explore the results of McScanX a popular synteny and collinearity detection toolkit and generate publication ready images.

SynVisio requires two files to run:

The simplified gff file that was used as an input for a McScanX query.
The collinearity file generated as an output by McScanX for the same input query.
Optional track file in bedgraph format to annotate the generated charts.

SynVisio offers different types of visualizations such as Linear Parallel plots, Hive plots, Stacked Parallel Plots and Dot plots. Users can configure the type of plots required and then choose the source and the target chromosomes that need to be mapped. Users also have option to download the generated visualizations in publication ready SVG or PNG formats.

Address of the bookmark: https://synvisio.github.io/#/

Mugsy: multiple whole genome alignment tool

Jit — Fri, 08 Dec 2017 17:41:14 -0600

Mugsy is a multiple whole genome aligner. Mugsy uses Nucmer for pairwise alignment, a custom graph based segmentation procedure for identifying collinear regions, and the segment-based progressive multiple alignment strategy from Seqan::TCoffee. Mugsy accepts draft genomes in the form of multi-FASTA files and does not require a reference genome.

To cite Mugsy, use:

Angiuoli SV and Salzberg SL. Mugsy: Fast multiple alignment of closely related whole genomes.Bioinformatics 2011 27(3):334-4

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

Delta: a new Web-based 3D genome visualization and analysis platform

Jit — Wed, 20 Dec 2017 08:49:55 -0600

Delta is an integrative visualization and analysis platform to facilitate visually annotating and exploring the 3D physical architecture of genomes. Delta takes Hi-C or ChIA-PET contact matrix as input and predicts the topologically associating domains and chromatin loops in the genome. It then generates a physical 3D model which represents the plausible consensus 3D structure of the genome. Deltafeatures a highly interactive visualization tool which enhances the integration of genome topology/physical structure with extensive genome annotation by juxtaposing the 3D model with diverse genomic assay outputs.

https://github.com/zhangzhwlab/delta

Address of the bookmark: https://github.com/zhangzhwlab/delta

List of visualization tools for genome alignments

Rahul Nayak — Fri, 02 Feb 2018 13:25:33 -0600

Genome browsers are useful not only for showing final results but also for improving analysis protocols, testing data quality, and generating result drafts. Its integration in analysis pipelines allows the optimization of parameters, which leads to better results. But sometime, we need publication ready figure of genomes. Following are the list of genome alignment visualization tools, which could be useful for analysis and interpretation of results:

ABySS Explorer

Interactive Java application that uses a novel graph-based representation to display a sequence assembly and associated metadata

http://www.bcgsc.ca/platform/bioinfo/software/abyss-explorer

BamView

Genome browser and annotation tool that allows visualization of sequence features, next-generation sequencing (NGS) data and the results of analyses within the context of the sequence, and also its six-frame translation

http://www.sanger.ac.uk/resources/software/artemis/

DNannotator

Annotation web toolkit for regional genomic sequences

http://bioapp.psych.uic.edu/DNannotator.htm

JVM

Java Visual Mapping tool for NGS reads

http://www.springer.com/cda/content/document/cda_downloaddocument/9789401792448-c2.pdf?SGWID=0-0-45-1487072-p176815501

LookSeq

Web-based visualization of sequences derived from multiple sequencing technologies. Low- or high-depth read pileups and easy visualization of putative single nucleotide and structural variation

http://lookseq.sourceforge.net

MagicViewer

Visualization of short read alignment, identification of genetic variation and association with annotation information of a reference genome

http://bioinformatics.zj.cn/magicviewer/

MapView

Alignments of huge-scale single-end and pair-end short reads

http://omictools.com/mapview-s1367.html

MultiPipMaker

Computes alignments of similar regions in two DNA sequences. The resulting alignments are summarized with a ‘percent identity plot’ (pip)

http://pipmaker.bx.psu.edu/pipmaker/

PileLineGUI

Handling genome position files in NGS studies

http://sing.ei.uvigo.es/pileline/pilelinegui.html

SAMtools tview

Simple and fast text alignment viewer; NGS compatible

http://www.htslib.org/

SEWAL

Uses a locality-sensitive hashing algorithm to enumerate all unique sequences in an entire Illumina sequencing run

http://www.sourceforge.net/projects/sewal

STAR

A web-based integrated solution to management and visualization of sequencing data

http://wanglab.ucsd.edu/star/browser

SVA

Software for annotating and visualizing sequenced human genomes

http://www.svaproject.org

Viewer (IGV)

Visualization of large heterogeneous datasets, providing a smooth and intuitive user experience at all levels of genome resolution

https://www.broadinstitute.org/igv/

ZOOM Lite

NGS data mapping and visualization software

http://bioinfor.com/zoom/lite/

ChopStitch: exon annotation and splice graph construction using transcriptome assembly and whole genome sequencing data

Rahul Nayak — Tue, 03 Jul 2018 04:14:52 -0500

ChopStitch is a new method for finding putative exons and constructing splice graphs using an assembled transcriptome and whole genome shotgun sequencing (WGSS) data. ChopStitch identifies exon-exon boundaries in de novo assembled RNA-seq data with the help of a Bloom filter that represents the k-mer spectrum of WGSS reads. The algorithm also detects base substitutions in transcript sequences corresponding to sequencing or assembly errors, haplotype variations, or putative RNA editing events. The primary output of our tool is a FASTA file containing putative exons. Further, exon edges are interrogated for alternative exon-exon boundaries to detect transcript isoforms, which are reported as splice graphs in dot output format.

Address of the bookmark: https://github.com/bcgsc/ChopStitch

AirLift, a methodology and tool for comprehensively moving mappings and annotations from one genome to another similar genome

Jit — Mon, 23 Dec 2019 10:20:13 -0600

We propose AirLift, a methodology and tool for comprehensively moving mappings and annotations from one genome to another similar genome while maintaining the accuracy of a full mapper.

Address of the bookmark: https://github.com/CMU-SAFARI/AirLift

odgi: optimized dynamic genome/graph implementation

Abhimanyu Singh — Tue, 01 Feb 2022 23:42:21 -0600

odgi provides an efficient and succinct dynamic DNA sequence graph model, as well as a host of algorithms that allow the use of such graphs in bioinformatic analyses.

Careful encoding of graph entities allows odgi to efficiently compute and transform pangenomes with minimal overheads. odgi implements a dynamic data structure that leveraged multi-core CPUs and can be updated on the fly.

The edges and path steps are recorded as deltas between the current node id and the target node id, where the node id corresponds to the rank in the global array of nodes. Graphs built from biological data sets tend to have local partial order and, when sorted, the deltas be small. This allows them to be compressed with a variable length integer representation, resulting in a small in-memory footprint at the cost of packing and unpacking.

The RAM and computational savings are substantial. In partially ordered regions of the graph, most deltas will require only a single byte.

Address of the bookmark: https://github.com/pangenome/odgi