BOL: Related items

PANDASEQ is a program to align Illumina reads, optionally with PCR primers embedded in the sequence, and reconstruct an overlapping sequence.

BioStar — Fri, 21 Sep 2018 10:19:52 -0500

Development packages for zlib and libbz2 are needed, as well as a standard compiler environment. On Ubuntu, this can be installed via:

sudo apt-get install build-essential libtool automake zlib1g-dev libbz2-dev pkg-config

On MacOS, the Apple Developer tools and Fink (or MacPorts or Brew) must be installed, then:

sudo fink install bzip2-dev pkgconfig

Address of the bookmark: https://github.com/neufeld/pandaseq

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

chromosight: Computer vision based program for pattern recognition in chromosome (Hi-C) contact maps

Jit — Mon, 23 Mar 2020 06:20:04 -0500

Python package to detect chromatin loops (and other patterns) in Hi-C contact maps.

Stable version with pip:

pip3 install --user chromosight

Stable version with conda:

conda install -c bioconda -c conda-forge chromosight

or, if you want to get the latest development version:

pip3 install --user -e git+https://github.com/koszullab/chromosight.git@master#egg=chromosight

Address of the bookmark: https://github.com/koszullab/Chromosight

CGView.js is a Circular Genome Viewing tool

LEGE — Wed, 27 Mar 2024 11:16:24 -0500

CGView.js is a Circular Genome Viewing tool for visualizing and interacting with small genomes. This software is an adaptation of the Java program CGView.

CGView.js is the genome viewer of Proksee, an expert system for genome assembly, annotation and visualization.

Features

Circular and linear views of genomes
Capable of drawing genomes up to 10 Mbp with 1000's of features and 100's contigs
Smooth zooming down to the sequence level
Easily generate features and plots directly form the sequence (e.g. ORFs, GC-content and GC-Skew)
Save high resolution PNG maps up to 8000x8000px
Fully documented API for interacting with CGView.js maps

Address of the bookmark: https://js.cgview.ca/

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

Chromonomer: a tool set for repairing and enhancing assembled genomes through integration of genetic maps and conserved synteny

Jit — Mon, 17 Feb 2020 05:38:46 -0600

Chromonomer is a program designed to integrate a genome assembly with a genetic map. Chromonomer tries very hard to identify and remove markers that are out of order in the genetic map, when considered against their local assembly order; and to identify scaffolds that have been incorrectly assembled according to the genetic map, and split those scaffolds.

Address of the bookmark: http://catchenlab.life.illinois.edu/chromonomer/

EXCAVATOR: detecting copy number variants from whole-exome sequencing data

Radha Agarkar — Fri, 04 Jan 2019 10:10:48 -0600

EXCAVATOR, for the detection of copy number variants (CNVs) from whole-exome sequencing data. EXCAVATOR combines a three-step normalization procedure with a novel heterogeneous hidden Markov model algorithm and a calling method that classifies genomic regions into five copy number states. We validate EXCAVATOR on three datasets and compare the results with three other methods. These analyses show that EXCAVATOR outperforms the other methods and is therefore a valuable tool for the investigation of CNVs in largescale projects, as well as in clinical research and diagnostics. EXCAVATOR is freely available at http://sourceforge.net/projects/excavatortool/.

EXCAVATOR is a novel software package for the detection of copy number variants (CNVs) from whole-exome sequencing data.
EXCAVATOR has been published on Genome Biology (http://genomebiology.com/2013/14/10/R120/abstract).

Address of the bookmark: https://sourceforge.net/projects/excavatortool/

chromeister: An ultra fast, heuristic approach to detect conserved signals in extremely large pairwise genome comparisons.

Jit — Thu, 03 Feb 2022 04:01:55 -0600

chromeister: An ultra fast, heuristic approach to detect conserved signals in extremely large pairwise genome comparisons.

USAGE:

-query: sequence A in fasta format
-db: sequence B in fasta format
-out: output matrix
-kmer Integer: k>1 (default 32) Use 32 for chromosomes and genomes and 16 for small bacteria
-diffuse Integer: z>0 (default 4) Use 4 for everything - if using large plant genomes you can try using 1
-dimension Size of the output matrix and plot. Integer: d>0 (default 1000) Use 1000 for everything that is not full genome size, where 2000 is recommended

Address of the bookmark: https://github.com/estebanpw/chromeister

BioGPS: Spotlight on the Gene Expression Atlas

Jit — Thu, 18 Oct 2018 12:15:12 -0500

BioGPS opened 2016 with a publication in Nucleic Acids Research, right after the New Year holiday. Throughout the year, new designs for the site were being created, reviewed, adjusted, reviewed, adjusted, and more review/adjustments in anticipation of a site redesign for 2017. A Plugin registration Blitz was held in March and April; followed by a Plugin Review Blitz in May. The BioGPS spotlight series was also restarted, with spotlights on BGEE, Intermine, and other Intermine-related plugins.

There were ~910,000 requests made to BioGPS in 2016. Requests to BioGPS peaked in March and at the lowest in December.

Address of the bookmark: http://biogps.org/

RNA-seq workflow: gene-level exploratory analysis and differential expression

Jit — Sat, 09 Oct 2021 07:59:23 -0500

Here we walk through an end-to-end gene-level RNA-seq differential expression workflow using Bioconductor packages. We will start from the FASTQ files, show how these were quantified to the reference transcripts, and prepare gene-level count datasets for downstream analysis. We will perform exploratory data analysis (EDA) for quality assessment and to explore the relationship between samples, perform differential gene expression analysis, and visually explore the results.

Address of the bookmark: http://master.bioconductor.org/packages/release/workflows/vignettes/rnaseqGene/inst/doc/rnaseqGene.html