BOL: Related items

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

Upcoming R Webinar

Jitendra Narayan — Wed, 11 Sep 2013 10:30:16 -0500

This webinar will describe an R based approach to considerably speed GWAS computation time on a notebook book computer.

More http://www.extension.org/pages/68354/upcoming-webinar:-fast-semi-parallel-linear-and-logistic-regression-for-genome-wide-association-studi#.UjCL9azyPqV

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.

FUMA GWAS: Functional Mapping and Annotation of Genome-Wide Association Studies

Jit — Sat, 01 Jun 2019 03:11:16 -0500

FUMA is a platform that can be used to annotate, prioritize, visualize and interpret GWAS results.
The SNP2GENE function takes GWAS summary statistics as an input, and provides extensive functional annotation for all SNPs in genomic areas identified by lead SNPs.
The GENE2FUNC function takes a list of gene IDs (as identified by SNP2GENE or as provided manually) and annotates genes in biological context

Address of the bookmark: https://fuma.ctglab.nl/

Postdoctoral Associate - Bioinformatics at Duke University Medical Center

Sat, 10 Aug 2013 18:38:38 -0500

The Department of Biostatistics and Bioinformatics at Duke University Medical Center is seeking a Postdoctoral Associate for a one year appointment to work on several high-dimensional research projects. The specific goals of the project are to identify genes or molecular markers that are predictive of clinical outcomes in renal and prostate cancer.

Candidates must have: a PhD degree in statistics, biostatistics or bioinformatics, extensive experience in analyzing high-dimensional data (microarray, SNP, CNVs) and of validation approaches. In addition, experience in penalized regression methods, data base manipulation; and strong programming skills in order to conduct Monte Carlo studies and applications (R). Candidate must have excellent communication skills (verbal, written and presentation), a strong proficiency in Linux system.

This position is available immediately and will be filled as soon as possible. Appointment could be extended beyond the first year based on additional funding.

For more information about the Department of Biostatistics and Bioinformatics, please visit our website: http://www.biostat.duke.edu.

For more info: http://biostat.duke.edu/sites/biostat.duke.edu/files/Halabi%20-%20Postdoc%20Job%20Posting%202013%20updated.pdf

Duke University is an Equal Opportunity/Affirmative Action Employer.

Venn Diagrams on R Studio

Jitendra Prajapati — Mon, 25 Apr 2016 16:22:28 -0500

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

EWAS: epigenome-wide association study software 2.0

Jit — Wed, 21 Mar 2018 18:14:00 -0500

EWAS2.0 can analyze EWAS data and identify the association between epigenetic variations and disease/phenotype. On the basis of EWAS1.0, we have added more distinctive features. EWAS2.0 software was developed based on our “population epigenetic framework” and can perform: (1) epigenome-wide single marker association study; (2) epigenome-wide methylation haplotype (meplotype) association study; and (3) epigenome-wide association meta-analysis.

Address of the bookmark: http://www.bioapp.org/ewas/

RNA Sequencing Helps Identify Functional Variants from GWAS

Andaleeb — Fri, 22 Nov 2013 21:33:33 -0600

For Alzheimer’s and other complex disorders, mining the genome for disease-associated variants is no longer the obstacle. The challenge nowadays is figuring out how the identified loci relate to disease. As reported last month in Nature and its associated journals, advances in high-throughput RNA sequencing are providing new tools for understanding how disease loci influence gene expression—a starting point for understanding their connection to pathogenesis.

Address of the bookmark: http://schizophreniaforum.org/new/detail.asp?id=1953

CAUSEL: an epigenome- and genome-editing pipeline for establishing function of noncoding GWAS variants

BioJoker — Tue, 09 Apr 2019 07:23:37 -0500

Validated a widely accessible approach that can be used to establish functional causality for noncoding sequence variants identified by GWASs.

https://www.nature.com/articles/nm.3975

Address of the bookmark: https://www.nature.com/articles/nm.3975

DADA2: Fast and accurate sample inference from amplicon data with single-nucleotide resolution

Jit — Tue, 10 Nov 2020 20:26:00 -0600

The DADA2 tutorial goes through a typical workflow for paired end Illumina Miseq data: raw amplicon sequencing data is processed into the table of exact amplicon sequence variants (ASVs) present in each sample.

The DADA2 Workflow on Big Data goes through workflow optimized to run on large datasets (10s of millions to billions of reads).

An ITS-specific version of the DADA2 workflow identifies and verifiably removes primers on both ends of each ITS read, a key step due to the variable length of the ITS region.

Short demonstrations of assigning taxonomy and assigning species to sequences.

Address of the bookmark: https://benjjneb.github.io/dada2/index.html