BOL: Related items

RNA-seq Analysis Workshop Course Materials

Jit — Tue, 03 Jul 2018 08:14:14 -0500

RNAseq can be roughly divided into two "types": Reference genome-based - an assembled genome exists for a species for which an RNAseq experiment is performed. It allows reads to be aligned against the reference genome and significantly improves our ability to reconstruct transcripts. This category would obviously include humans and most model organisms but excludes the majority of truly biologically intereting species (e.g., Hyacinth macaw); Reference genome-free - no genome assembly for the species of interest is available. In this case one would need to assemble the reads into transcripts using de novo approaches. This type of RNAseq is as much of an art as well as science because assembly is heavily parameter-dependent and difficult to do well. In this lesson we will focus on the Reference genome-based type of RNA seq. http://chagall.med.cornell.edu/RNASEQcourse/

Address of the bookmark: http://chagall.med.cornell.edu/RNASEQcourse/

An Introduction to Applied Bioinformatics

Jit — Fri, 02 Mar 2018 04:26:38 -0600

IAB is primarily being developed by Greg Caporaso(GitHub/Twitter: @gregcaporaso) in the Caporaso Lab at Northern Arizona University. You can find information on the courses I teach on my teaching website and information on my research and lab on my lab website.

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

GWASpro: A High-Performance Genome-Wide Association Analysis Server

Rahul Nayak — Fri, 07 Dec 2018 08:04:57 -0600

GWASpro supports building complex design matrices, by which complex experimental designs that may include replications, treatments, locations and times, can be accounted for in the linear mixed model (LMM). GWASpro is optimized to handle GWAS data that may consist of up to 10 million markers and 10,000 samples from replicable lines or hybrids. GWASpro provides an interface that significantly reduces the learning curve for new GWAS investigators.

Address of the bookmark: https://bioinfo.noble.org/GWASPRO/

SciLifeLab tutorial for bioinformatics analysis !

Jit — Tue, 17 Apr 2018 04:33:00 -0500

SciLifeLab is a national center for molecular biosciences with focus on health and environmental research.

Courses

Old courses (2012-2014)

Jvarkit : Java utilities for Bioinformatics

Jit — Fri, 08 Jun 2018 09:31:55 -0500

Collection of Java tool kits for bioinformatics works: Jvarkit : Java utilities for Bioinformatics

Address of the bookmark: http://lindenb.github.io/jvarkit/

Bactopia: a Flexible Pipeline for Complete Analysis of Bacterial Genomes

Abhi — Wed, 15 May 2024 14:36:12 -0500

Bactopia is a flexible pipeline for complete analysis of bacterial genomes. The goal of Bactopia is to process your data with a broad set of tools, so that you can get to the fun part of analyses quicker!

Bactopia can be split into two main parts: Bactopia Analysis Pipeline, and Bactopia Tools.

Bactopia Analysis Pipeline is the main per-isolate workflow in Bactopia. Built with Nextflow, input FASTQs (local or available from SRA/ENA) are put through numerous analyses including: quality control, assembly, annotation, minmer sketch queries, sequence typing, and more.

Bactopia Tools are a set a independent workflows fo

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

Senior Bioinformatics Scientist @ Strand Life Sciences -- Bangalore, India

Wed, 02 Jan 2019 09:23:49 -0600

RESPONSIBILITIES
The candidate is expected to work on a variety of projects related to analysis of data from NGS, Mass Spectrometry, Flow Cytometry and other related modalities. The position expects hands-on work and a strong eye for detail. The candidate will be able to contribute to impactful work spanning patient care, clinical research, and new assay and method development.
REQUIREMENTS
A PhD in a quantitative field (statistics, math, bioinformatics, computer science, physics or similar) and work experience or post-doc experience handling high throughout genomics data.
PREFERENCES
Experience in working in inter-disciplinary groups and ability to author research publications are additional desired qualities.
LOCALE
The position is in Bangalore and reports to the Chief Scientific Officer.
HOW TO APPLY
Write to ramesh[at]strandls.com.

Mesquite: A modular system for evolutionary analysis

Rahul Nayak — Tue, 18 Jul 2017 07:42:46 -0500

Mesquite is modular, extendible software for evolutionary biology, designed to help biologists organize and analyze comparative data about organisms. Its emphasis is on phylogenetic analysis, but some of its modules concern population genetics, while others do non-phylogenetic multivariate analysis. Because it is modular, the analyses available depend on the modules installed.

http://mesquiteproject.wikispaces.com/

Address of the bookmark: https://github.com/MesquiteProject/MesquiteCore/releases

Bioinformatics Training Courses At RASA LSI

RASA Life Sciences — Wed, 06 Nov 2019 00:30:51 -0600

RASA conducts comprehensive Life Science skill development training courses in Pune, India for working professionals, researchers, students and job-seeker. The trainings are crafted meticulously, covering different modules of courses such as Bioinformatics course, In silico Drug Discovery course, Next Generation Sequence data analysis course, Molecular Biology & Life science software development course wherein you learn from industry leaders how to apply these skills in life science & have a command over software developing process by using various methodologies. We conduct in-class training and instructor-led live online classes worldwide, along with corporate and skill development training worldwide.

Workshops are conducted in regular intervals on Drug Designing, Protein Modeling and Simulation, Chemoinformatics, Bioinformatics etc.The workshops are highly beneficial for working professionals, students, researcher for enhancements of the skills in short duration.

RNAseq data analysis links !

Robert M Willioms — Mon, 27 Nov 2017 16:28:11 -0600

RNA-sequencing (RNA-seq) has a wide variety of applications, but no single analysis pipeline can be used in all cases. We review all of the major steps in RNA-seq data analysis, including experimental design, quality control, read alignment, quantification of gene and transcript levels, visualization, differential gene expression, alternative splicing, functional analysis, gene fusion detection and eQTL mapping.

A survey of best practices for RNA-seq data analysis

RNA-seq workflow: gene-level exploratory analysis and DE

RNAseq analysis notes from Tommy Tang

Analysis of RNA ‐ Seq Data

RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR

Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks.

EBI RNA-Seq exercise

An open RNA-Seq data analysis pipeline tutorial with an example

RNA-Seq Analysis Workflow

Transcript-level expression analysis of RNA-seq experiments