<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/39114?offset=20 https://bioinformaticsonline.com/bookmarks/view/27850/clusterprofiler Thu, 16 Jun 2016 18:57:03 -0500 https://bioinformaticsonline.com/bookmarks/view/27850/clusterprofiler <![CDATA[clusterProfiler]]> statistical analysis and visulization of functional profiles for genes and gene clusters

Bioconductor version: Release (3.3)

This package implements methods to analyze and visualize functional profiles (GO and KEGG) of gene and gene clusters.

Author: Guangchuang Yu <guangchuangyu at gmail.com> with contributions from Li-Gen Wang and Giovanni Dall'Olio.

Maintainer: Guangchuang Yu <guangchuangyu at gmail.com>

Citation (from within R, enter citation("clusterProfiler")):

Yu G, Wang L, Han Y and He Q (2012). “clusterProfiler: an R package for comparing biological themes among gene clusters.” OMICS: A Journal of Integrative Biology, 16(5), pp. 284-287.
Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("clusterProfiler")

https://www.bioconductor.org/packages/devel/bioc/vignettes/clusterProfiler/inst/doc/clusterProfiler.html

Address of the bookmark: https://www.bioconductor.org/packages/devel/bioc/vignettes/clusterProfiler/inst/doc/clusterProfiler.html

]]> Jit https://bioinformaticsonline.com/bookmarks/view/44663/svbyeye-r-package-to-visualize-alignments-between-two-or-multiple-dna-sequences Tue, 17 Sep 2024 02:34:57 -0500 https://bioinformaticsonline.com/bookmarks/view/44663/svbyeye-r-package-to-visualize-alignments-between-two-or-multiple-dna-sequences <![CDATA[SVbyEye: R Package to visualize alignments between two or multiple DNA sequences]]> R Package to visualize alignments between two or multiple DNA sequences including
a number of functionalities to facilitate processing of alignments in PAF format.

SVbyEye, an open-source R package to visualize and annotate sequence-to-sequence alignments along with various functionalities to process alignments in PAF format. The tool facilitates the characterization of complex SVs in the context of sequence homology helping resolve the mechanisms underlying their formation. Availability and implementation SVbyEye is available at https://github.com/daewoooo/SVbyEye.

Author: David Porubsky

Address of the bookmark: https://github.com/daewoooo/SVbyEye

]]> LEGE https://bioinformaticsonline.com/blog/view/37049/chromomap-an-r-package-for-interactive-visualization-and-mapping-of-human-chromosomes Mon, 25 Jun 2018 17:22:24 -0500 https://bioinformaticsonline.com/blog/view/37049/chromomap-an-r-package-for-interactive-visualization-and-mapping-of-human-chromosomes <![CDATA[chromoMap-An R package for Interactive visualization and mapping of human chromosomes]]> chromoMap is an R package that provides interactive, configurable and elegant graphics visualization of the human chromosomes allowing users to map chromosome elements (like genes, SNPs etc.) on the chromosome plot. It introduces a special plot viz. the "chromosome heatmap" that, in addition to mapping elements, can visualize the data associated with chromosome elements (like gene expression) in the form of heat colors which can be highly advantageous in the scientific interpretations and research work. Because of the enormous size of the chromosomes, it is impractical to visualize each element on the same plot. But chromoMap plots provide a magnified view for each of chromosome location to render additional information and visualization specific for that location. You can map thousands of genes and can view all mappings easily. Users can investigate the detailed information about the mappings (like gene names or total genes mapped on a location) or can view the magnified single or double stranded view of the chromosome at a location showing each mapped element in sequential order (You will see in the demos below). Not ony that, the plots can be saved as HTML documents that can be customized and shared easily. In addition, you can include them in R Markdown or in R Shiny applications.

https://cran.r-project.org/web/packages/chromoMap/index.html

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/38541/geneoverlap-an-r-package-to-test-and-visualize-gene-overlaps Thu, 27 Dec 2018 19:45:52 -0600 https://bioinformaticsonline.com/bookmarks/view/38541/geneoverlap-an-r-package-to-test-and-visualize-gene-overlaps <![CDATA[GeneOverlap: An R package to test and visualize gene overlaps]]> Overlapping gene lists can reveal biological meanings and may lead to novel hypotheses. For example, histone modification is an important cellular mechanism that can pack and re-pack chromatin. By making the chromatin structure more dense or loose, the gene expression can be turned on or off. Tri-methylation on lysine 4 of histone H3 (H3K4me3) is associated with gene activation and its genome-wide enrichment can be mapped by using ChIP-seq experiments. Because of its activating role, if we overlap the genes that are bound by H3K4me3 with the genes that are highly expressed, we should expect a positive association. Similary, we can perform such kind of overlapping between the gene lists of different histone modifications with that of various expression groups and establish each histone modification’s role in gene regulation.

Address of the bookmark: https://bioconductor.org/packages/release/bioc/vignettes/GeneOverlap/inst/doc/GeneOverlap.pdf

]]> Jit https://bioinformaticsonline.com/bookmarks/view/42012/phewas-r-package-is-designed-to-provide-an-accessible-interface-to-the-phenome-wide-association-study Thu, 30 Jul 2020 22:06:37 -0500 https://bioinformaticsonline.com/bookmarks/view/42012/phewas-r-package-is-designed-to-provide-an-accessible-interface-to-the-phenome-wide-association-study <![CDATA[PheWAS: R package is designed to provide an accessible interface to the phenome wide association study]]> The PheWAS R package is designed to provide an accessible interface to the phenome wide association study. For a description of the methods available and some simple examples, please see the package vignette or the R documentation. For installation help, see below. ##Installing the PheWAS Package The PheWAS package can be installed using the devtools package. The following code when executed in R will get you started:

install.packages("devtools")
#It may be necessary to install required as not all package dependencies are installed by devtools:
install.packages(c("dplyr","tidyr","ggplot2","MASS","meta","ggrepel","DT"))
devtools::install_github("PheWAS/PheWAS")
library(PheWAS)

Address of the bookmark: https://github.com/PheWAS/PheWAS

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/27070/venn-diagrams-on-r-studio Mon, 25 Apr 2016 16:22:28 -0500 https://bioinformaticsonline.com/bookmarks/view/27070/venn-diagrams-on-r-studio <![CDATA[Venn Diagrams on R Studio]]> First step: Install & load “VennDiagram” package. 
# install.packages('VennDiagram')
library(VennDiagram)

Second step: Load data

Add filepath if “catdoge.csv” is not in working-directory.

d <- read.csv("catdoge.csv")

Address of the bookmark: http://rstudio-pubs-static.s3.amazonaws.com/13301_6641d73cfac741a59c0a851feb99e98b.html

]]> Jitendra Prajapati https://bioinformaticsonline.com/videolist/watch/16685/webinar-blast-in-the-cloud Mon, 15 Sep 2014 17:29:32 -0500 https://bioinformaticsonline.com/videolist/watch/16685/webinar-blast-in-the-cloud <![CDATA[Webinar: BLAST in the Cloud]]> Presented July 30, 2014 and covering: an NCBI BLAST AMI at Amazon Web Services; introduction to AWS and setting up an instance; running command line BLAST and using the BLAST URL API via the AMI; and answers to attendee questions.]]> https://bioinformaticsonline.com/blog/view/43424/rest-api Mon, 04 Oct 2021 12:46:40 -0500 https://bioinformaticsonline.com/blog/view/43424/rest-api <![CDATA[REST API]]> REST API

The Representational State Transfer (REST) sample clients are provided for a number of programming languages. For details of how to use these clients, download the client and run the program without any arguments.

Language
Download
Requirements
Perl psiblast.pl LWP and XML::Simple

Python

psiblast.py

 xmltramp2

For details see Environment setup for REST Web Services and Examples for Perl REST Web Services Clients pages.

]]> Neel https://bioinformaticsonline.com/bookmarks/view/40834/nucleus-python-and-c-code-for-reading-and-writing-genomics-data Sun, 02 Feb 2020 08:14:19 -0600 https://bioinformaticsonline.com/bookmarks/view/40834/nucleus-python-and-c-code-for-reading-and-writing-genomics-data <![CDATA[Nucleus: Python and C++ code for reading and writing genomics data.]]> Nucleus is a library of Python and C++ code designed to make it easy to read, write and analyze data in common genomics file formats like SAM and VCF. In addition, Nucleus enables painless integration with the TensorFlow machine learning framework, as anywhere a genomics file is consumed or produced, a TensorFlow tfrecords file may be used instead.

Address of the bookmark: https://github.com/google/nucleus

]]> Jit https://bioinformaticsonline.com/blog/view/42974/list-of-bioinformatics-packages-for-ngs-analysis Sat, 20 Mar 2021 00:28:51 -0500 https://bioinformaticsonline.com/blog/view/42974/list-of-bioinformatics-packages-for-ngs-analysis <![CDATA[List of bioinformatics packages for NGS analysis !]]> Package suites gather software packages and installation tools for specific languages or platforms. We have some for bioinformatics software.

  • Bioconductor – A plethora of tools for analysis and comprehension of high-throughput genomic data, including 1500+ software packages. [ paper-2004 | web ]
  • Biopython – Freely available tools for biological computing in Python, with included cookbook, packaging and thorough documentation. Part of the Open Bioinformatics Foundation. Contains the very useful Entrez package for API access to the NCBI databases. [ paper-2009 | web ]
  • Bioconda – A channel for the conda package manager specializing in bioinformatics software. Includes a repository with 3000+ ready-to-install (with conda install) bioinformatics packages. [ paper-2018 | web ]
  • BioJulia – Bioinformatics and computational biology infastructure for the Julia programming language. [ web ]
  • Rust-Bio – Rust implementations of algorithms and data structures useful for bioinformatics. [ paper-2016 ]
  • SeqAn – The modern C++ library for sequence analysis.
]]> Rahul Nayak