BOL: Related items

NovoGraph: building whole genome graphs from long-read-based de novo assemblies

Jit — Thu, 15 Nov 2018 12:48:30 -0600

NovoGraph: building whole genome graphs from long-read-based de novo assemblies

An algorithmically novel approach to construct a genome graph representation of long-read-based de novo sequence assemblies. We then provide a proof of principle by creating a genome graph of seven ethnically-diverse human genomes.

https://f1000research.com/articles/7-1391/v1

Address of the bookmark: https://github.com/NCBI-Hackathons/NovoGraph

Binding Site Prediction in Protein !

Poonam Mahapatra — Wed, 25 Apr 2018 04:35:57 -0500

The interaction between proteins and other molecules is fundamental to all biological functions. In this section we include tools that can assist in prediction of interaction sites on protein surface and tools for predicting the structure of the intermolecular complex formed between two or more molecules (docking).

Pockets Identification

CASTp

Automatic Identification of pockets and cavities in proteins structure, and quantitation of their volumes using Delaunay triangulation. Available also as PyMOL plugin

Pocket-Finder

Automatic identification of pockets and cavities in proteins structure, and quantitation of their volumes.

PocketPicker

Grid-based technique for the analysis of protein pockets. PocketPicker available as a plugin for PyMOL

Binding Site Prediction

ConSurf

Identification of functional regions in proteins by surface-mapping of phylogenetic information

CRESCENDO

Identification protein interaction sites. It uses sequence conservation patterns in homologous proteins to distinguish between residues that are conserved due to structural restraints from those due to functional restraints.

Ligand Binding Sites

3DLigandSite

The server utilizes protein-structure prediction to provide structural models of the binding site. Ligands bound to structures are superimposed onto the model and use to predict the binding site.

FINDSITE

A threading-based method for ligand-binding site prediction and functional annotation based on binding-site similarity across superimposed groups of threading templates.

LIGSITE^csc

Prediction of binding site by pocket identification using the Connolly surface and degree of conservation

metaPocketA meta server for ligand-binding site prediction. metaPocket use LIGSITE^csc, PASS, Q-SiteFinder and SURFNET

DISTRUCT: a program for the graphical display of population structure

Abhimanyu Singh — Mon, 25 Mar 2019 03:33:44 -0500

distruct is a program that can be used to graphically display results produced by the genetic clustering program structure or by other similar programs. The figures produced by distructdisplay individual membership coefficients in the same form as used in "Genetic structure of human populations" Science 298: 2381-2385 (2002). Various options enable the user to control left-to-right printing order of populations, bottom-to-top printing order of clusers, colors, and other graphical details. [Example]

[Download software package (includes the manual)] (you will be directed first to a registration page and we would very much appreciate if you register)
[Download manual]
[Download software note from Molecular Ecology Notes 4: 137-138 (2004)]

To use the UNIX versions, unzip and untar the files in an appropriate directory using

gunzip filename.tar.gz; tar xvf filename.tar

where "filename.tar.gz" is the downloaded file. Winzip will unzip the Windows version. Run the program by typing

./distruct

in UNIX or

distruct

from a Dos prompt in Windows. It will produce a figure using the data that are represented in the Central/South Asia K=5 plot in Science 298: 2381-2385 (2002).

Please send comments or problems with distruct to Noah Rosenberg.

October 15, 2014 — Users of Distruct may also find CLUMPP and CLUMPAK of interest.

Address of the bookmark: https://rosenberglab.stanford.edu/distruct.html

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

JBrowse 2: a modular genome browser with views of synteny and structural variation

Abhi — Tue, 25 Apr 2023 20:58:52 -0500

igvjs - a create-react-app with igv package from npm installed. the igv.js is instrumented to output "DONE" to the console when finished, and to have an increased fetchSizeLimit (which is otherwise git in CRAM longread tests)
jb2-web - stock instance of jbrowse-web v1.7.5
jb1 - stock instance of jbrowse 1 v1.16.11
jb2 embedded - a create-react-app with @jbrowse/react-linear-genome-view

Address of the bookmark: https://github.com/GMOD/jb2profile

Ensembl Variation - Calculated variant consequences

Jit — Sun, 09 Sep 2018 19:17:37 -0500

For each variant that is mapped to the reference genome, we identify all overlapping Ensembl transcripts. We then use a rule-based approach to predict the effects that each allele of the variant may have on each transcript. The set of consequence terms, defined by the Sequence Ontology (SO), that can be currently assigned to each combination of an allele and a transcript is shown in the table below. Note that each allele of each variant may have a different effect in different transcripts.

Address of the bookmark: https://www.ensembl.org/info/genome/variation/prediction/predicted_data.html