BOL: Related items

Graph Genome Suite

Jit — Fri, 28 Oct 2016 07:59:54 -0500

Seven Bridges is the biomedical data analysis company accelerating breakthroughs in genomics research for cancer, drug development and precision medicine. We build self-improving systems to analyze millions of genomes, including the Graph Genome Suite — the most advanced population genomics tools in the world.

Address of the bookmark: https://www.sbgenomics.com/graph/

Osprey: Network Visualization System

BioJoker — Sun, 20 Jan 2019 05:34:24 -0600

Osprey is a software platform for the visualization of complex biological interaction networks. Osprey builds data-rich graphical representations from Gene Ontology (GO) annotated interaction data maintained by the BioGRID.

Osprey is developed by the TyersLab and is a part of the BioGRID family of software. It utilizes both MySQL and Java to operate and is compatible with Windows, Linux, and Apple operating systems.

These works were published in Breitkreutz, BJ., Stark, C., Tyers M. "Osprey: A Network Visualization System." Genome Biology 2003 4(3):R22 [Genome Biology] [PDF] [PubMed] and supported by the National Institutes of Health, Canadian Institutes of Health Research, and Genome Canada.

Address of the bookmark: https://osprey.thebiogrid.org/

d3Network:Tools for creating D3 JavaScript network, tree, dendrogram, and Sankey graphs from R.

Jit — Fri, 06 Apr 2018 12:10:45 -0500

Mike Bostock’s D3.js is great for creating interactive network graphs with JavaScript. The d3Network package makes it easy to create these network graphs from R. The main idea is that you should able to take an R data frame with information about the relationships between members of a network and create full network graphs with one command.

Address of the bookmark: http://christophergandrud.github.io/d3Network/

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

ClipCrop: a tool for detecting structural variations with single-base resolution using soft-clipping information

Rahul Nayak — Thu, 04 Oct 2018 16:39:28 -0500

This is a tool for detecting structural variations using soft-clipping information From SAM files.

https://github.com/shinout/clipcrop

Address of the bookmark: https://github.com/shinout/clipcrop

GSP4PDB: a web tool to visualize, search and explore protein-ligand structural patterns

Neel — Sun, 15 Mar 2020 03:41:12 -0500

GSP4PDB is a user-friendly and efficient application to search and discover new patterns of protein-ligand interaction.

GSP4PDB is part of the services provided by the Bioinformatic Group of the University of Talca

http://gdblab.com/gsp4pdb/gsp4pdb2/

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3352-x

Address of the bookmark: http://gdblab.com/gsp4pdb/gsp4pdb2/

Syri compares alignments between two chromosome-level assemblies and identifies synteny and structural rearrangements.

Shruti Paniwala — Wed, 01 Jun 2022 02:01:13 -0500

Syri compares alignments between two chromosome-level assemblies and identifies synteny and structural rearrangements.

Address of the bookmark: https://github.com/schneebergerlab/syri

Hagfish - assess an assembly through creative use of coverage plots

Abhi — Fri, 20 May 2016 19:08:17 -0500

Hagfish is a tool that is to be used in data analysis of Next Generation Sequencing (NGS) experiments. Hagfish builds on the concept of coverage plots and aims to assist (amongst others) in quality control of de novo genome assembly or identification of structural variation in a genome re-sequencing experiment.

Hagfish requires a reference sequence and a paired end re-sequencing data set. Hagfish has more power the larger the insert size of the paired end library is.

Quick links: Installation,Operation, Read mappers, Hagfish scripts, Hagfish plots

Address of the bookmark: https://github.com/mfiers/hagfish

Software and Tools to detect structure variation with long reads !!

Archana Malhotra — Wed, 15 Mar 2017 14:31:09 -0500

Uncovering the connection between genetics and heritable diseases requires an approach that looks at all the variant bases and types in a genome. While a PacBio de novo assembly resolves the most novel SV variants. 8-10X PacBio coverage of single genomes or trios reveals triple the SVs detectable by short-read data.

With Single Molecule, Real-Time (SMRT) Sequencing, you can access structural variations having a broad range of sizes, types, and GC content with the ability to:

Uncover missing heritability linked to structural variation
Unambiguously identify genomic context and variant breakpoints at the sequence level to unravel the genetic etiology of disease
Resolve structural variation across the complete size spectrum with basepair resolution

Following are the SV tools, which can assist you to achieve your goal.

Sniffles: Structural variation caller using third generation sequencing

Sniffles is a structural variation caller using third generation sequencing (PacBio or Oxford Nanopore). It detects all types of SVs using evidence from split-read alignments, high-mismatch regions, and coverage analysis. Please note the current version of Sniffles requires sorted output from BWA-MEM (use -M and -x parameter) or NGM-LR with the optional SAM attributes enabled!

More at https://github.com/fritzsedlazeck/Sniffles

MultiBreak-SV: It identifies structural variants from next-generation paired end data, third-generation long read data, or data from a combination of sequencing platforms.

There are two pieces of software in this release: (1) a pre-processor that takes machineformat (.m5) BLASR files, and (2) MultiBreak-SV. For installation and usage instructions, see doc/MultiBreakSV-Manual.txt.

More at https://github.com/raphael-group/multibreak-sv

Parliament: A Structural Variation Tool. Why ask a single sv-detection approach to find every variant when you can have a parliament of tools deciding?

Publication about the algorithm and “…the first long-read characterization of structural variation in a diploid human personal genome…” (HS1011) - “Assessing structural variation in a personal genome—towards a human reference diploid genome”

More at https://sourceforge.net/projects/parliamentsv/

https://www.dnanexus.com/papers/Parliament_Info_Sheet.pdf

PBHoney: the structural variation discovery tool

PBHoney is an implementation of two variant-identification approaches designed to exploit the high mappability of long reads (i.e., greater than 10,000 bp). PBHoney considers both intra-read discordance and soft-clipped tails of long reads to identify structural variants.

Read The Paper http://www.biomedcentral.com/1471-2105/15/180/abstract

More at https://sourceforge.net/projects/pb-jelly/

SMRT-SV: Structural variant and indel caller for PacBio reads

Structural variant (SV) and indel caller for PacBio reads based on methods from Chaisson et al. 2014.

SMRT-SV provides an official software package for tools described in Chaisson et al. 2014 and adds several key features including the following.

Unified variant calling user interface with built-in cluster compute support
Small indel calling (2-49 bp)
Improved inversion calling (screenInversions)
Quality metric for SV calls based on number of local assemblies supporting each call
Higher sensitivity for SV calls using tiled local assemblies across the entire genome instead of "signature" regions
Genotyping of SVs with Illumina paired-end reads from WGS samples

More at https://github.com/EichlerLab/pacbio_variant_caller

Resolving the complexity of the human genome using single-molecule sequencing

Rahul Agarwal — Sat, 11 Jul 2015 12:47:34 -0500

The human genome is arguably the most complete mammalian reference assembly yet more than 160 euchromatic gaps remain and aspects of its structural variation remain poorly understood ten years after its completion. The results in this paper https://www.genomeweb.com/sequencing/team-uses-single-molecule-sequencing-close-gaps-chart-complexity-human-reference suggest a greater complexity of the human genome in the form of variation of longer and more complex repetitive DNA that can now be largely resolved with the application of this longer-read sequencing technology.

Address of the bookmark: http://www.nature.com/nature/journal/v517/n7536/full/nature13907.html