BOL: Related items

plumber:An R package that converts your existing R code to a web API

BioJoker — Wed, 13 Mar 2019 19:20:10 -0500

plumber allows you to create a REST API by merely decorating your existing R source code with special comments. Take a look at an example.

# plumber.R

#* Echo back the input
#* @param msg The message to echo
#* @get /echo
function(msg=""){
  list(msg = paste0("The message is: '", msg, "'"))
}

#* Plot a histogram
#* @png
#* @get /plot
function(){
  rand <- rnorm(100)
  hist(rand)
}

#* Return the sum of two numbers
#* @param a The first number to add
#* @param b The second number to add
#* @post /sum
function(a, b){
  as.numeric(a) + as.numeric(b)
}

Address of the bookmark: https://www.rplumber.io/

radar charts with ggplot2

Rahul Nayak — Tue, 17 Sep 2019 23:01:28 -0500

ggradar allows you to build radar charts with ggplot2. This package is based on Paul Williamson’s code, with new aesthetics and compatibility with ggplot2 2.0.

It was inspired by d3radaR, an htmlwidget built by timelyportfolio.

Address of the bookmark: https://github.com/ricardo-bion/ggradar

EFS: an ensemble feature selection tool implemented as R-package and web-application

Jit — Tue, 28 Jan 2020 05:12:23 -0600

The software EFS (Ensemble Feature Selection) makes use of multiple feature selection methods and combines their normalized outputs to a quantitative ensemble importance. Currently, eight different feature selection methods have been integrated in EFS, which can be used separately or combined in an ensemble.

https://biodatamining.biomedcentral.com/articles/10.1186/s13040-017-0142-8

Address of the bookmark: http://efs.heiderlab.de/

Postdoctoral scientist genome analytics/ genome bioinformatics (m/f/*)

Sun, 16 Feb 2020 02:57:40 -0600

https://www.uksh.de/jobs/Stellenangebote-nr-20190570-p-8.html
Your profile:
Degree in bioinformatics, biostatistics, or equivalent
Experience in the processing and analysis of large-scale genomics data using compute clusters / high-performance computing
Strong competence in working in Unix/Linux environments (shell)
Strong programming skills (in particular: Python, R, Perl)
Experience with using git and snakemake
Fluent English language skills, both spoken and written
Strong communication skills and motivation to work in a young, interdisciplinary, dynamic team

Additional Information:

If you have any questions about scientific aspects of this position, please contact Prof. Lars Bertram, head of LIGA (lars.bertram@uni-luebeck.de).

Please contact Ms. Anna Wolbert for further questions about administrative details (recruiting@uksh.de).

Weitere Informationen erhalten Sie auch unter www.uksh.de/karriere.

Wir freuen uns auf Ihre Bewerbung bis zum 15.03.2020 unter Angabe unserer Ausschreibungsnummer 20190570.119.CL.

PheWAS: R package is designed to provide an accessible interface to the phenome wide association study

BioStar — Thu, 30 Jul 2020 22:06:37 -0500

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

Introduction to phylogenies in R

Abhi — Wed, 13 Oct 2021 02:27:21 -0500

R phylogenetics is built on the contributed packages for phylogenetics in R, and there are many such packages. Let's begin today by installing a few critical packages, such as ape, phangorn, phytools, and geiger. To get the most recent CRAN version of these packages, you will need to have R 3.3.x installed on your computer!

Address of the bookmark: http://www.phytools.org/Cordoba2017/ex/2/Intro-to-phylogenies.html

R Package for PCA Analysis

LEGE — Sun, 24 Mar 2024 20:06:24 -0500

An R package for performing principal component analysis (PCA) of genomics data. The package performs PCA, generates the publication-ready plots, and identifies population-specific outlier individuals. The package can be accessed on GitHub: https://github.com/Devashish13/PopulationStructure

Address of the bookmark: https://rpubs.com/Devashish13/PCAGenomics

You and your friend have similar DNA !!!

Jit — Sun, 27 Jul 2014 20:44:05 -0500

New research out of Massachusetts claims that people often choose friends that are similar to them in genetics and they are more accurate than you might suppose. A study published on PNAS http://www.pnas.org/content/111/Supplement_3/10796.full found that people are apt to pick friends who are genetically similar to themselves - so much so that friends tend to be as alike at the genetic level as a person's fourth cousin.

Scientists with a long-running Framingham Heart Study looked at 1,932 people (examination of about 1.5 million markers of genetic variations), comparing unrelated friends to unrelated strangers. They found that friends shared about 1% of their genes — a percentage much higher than those shared with strangers.This new findings made it clear that people have more DNA in common with those who are selected as friends than with strangers in the same population.

The genes that lined up the most were olfactory genes, which deal with smell. The ones that lined up the least were immune system genes. The researchers weren't sure why that happened :/. Olfactory genes might be a straightforward explanation: People who like the same smells tend to be drawn to similar environments, where they meet others with the same tendencies.

Reference:

http://www.pnas.org/content/111/Supplement_3/10796.full

Image : http://i.kinja-img.com

AccNET

Jitendra Narayan — Fri, 07 Oct 2016 05:22:11 -0500

AccNET is a Perl application that presents a new way to study the accessory genome of a given set of organisms. Using the proteomes of these organisms, AccNET create a bipartite network compatible with common network analysis platforms. AccNET collects phylogenetic and functional information in a network improving the analysis capability. Networks offer a new perspective of organism organization through elements acquired by horizontal gene transfers and not constricted by hierarchical structures.

More at https://www.youtube.com/watch?v=vdGuy1GAJrQ

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

A5-miseq

Jit — Thu, 18 Aug 2016 04:05:23 -0500

_A5-miseq_ is a pipeline for assembling DNA sequence data generated on the Illumina sequencing platform. This README will take you through the steps necessary for running _A5-miseq_.

Point to note:

There are many situations where A5-miseq is not the right tool for the job. In order to produce accurate results, A5-miseq requires Illumina data with certain characteristics. A5-miseq will likely not work well with Illumina reads shorter than around 80nt, or reads where the base qualities are low in all or most reads before 60nt. A5-miseq assumes it is assembling homozygous haploid genomes. Use a different assembler for metagenomes and heterozygous diploid or polyploid organisms. Use a different assembler if a tool like FastQC reports your data quality is dubious. You have been warned! Datasets consisting solely of unpaired reads are not currently supported.

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