BOL: Related items

Google Genomics

Tenzin Paul — Thu, 18 Dec 2014 11:05:42 -0600

Explore genetic variation interactively. Compare entire cohorts in seconds with SQL-like queries. Compute transition/transversion ratios, genome-wide association, allelic frequency and more.
Process big genomic data easily. Run batch analyses like principal component analysis and Hardy-Weinberg equilibrium on as many samples as you like, in minutes or hours, with just a little code.
Use Google's infrastructure and big data expertise. Store one genome or a million using Google Genomics and take advantage of the same infrastructure that powers Search, Maps, YouTube, Gmail and Drive.
Support emerging global standards. Google Genomics is implementing the API defined by the Global Alliance for Genomics and Health for visualization, analysis and more. Compliant software can access Google Genomics, local servers, or any other implementation.

Address of the bookmark: https://cloud.google.com/genomics/

Comparative Genomics in Ensembl

Wed, 21 Jan 2015 08:31:11 -0600

The Ensembl browser provides viewable whole-genome alignments, homologues and phylogenetic gene trees, protein families, and ancestral sequences. Learn how to view and export these data in this video.

R for Microsoft Excel

Jitendra Narayan — Wed, 18 Feb 2015 00:43:27 -0600

If you currently use a spreadsheet like Microsoft Excel for data analysis, you might be interested in taking a look at this tutorial on how to transition from Excel to R by Tony Ojeda. The tutorial explains how to use R functions in place of Excel formulas, including tools like =AVERAGE and =VLOOKUP. For the most part, it uses modern R packages to keep the R code clear and concise.

You'll likely still be using Excel as a data source, though, so you'll also want to check out this guide to importing data from Excel to R from MilanoR.

Reference http://www.r-bloggers.com/an-r-tutorial-for-microsoft-excel-users/

A guide for complete R beginners :- R Syntax

Archana Malhotra — Fri, 20 Feb 2015 23:41:03 -0600

R is a functional based language, the inputs to a function, including options, are in brackets. Note that all dat and options are separated by a comma

Function(data, options)

Even quit is a function

So is help

help(read.table)

Provides the help page for the FUNCTION ‘read.table’

help.search(“t test”)

Searches for help pages that might relate to the phrase ‘t test’

NOTE: quotes are needed for search strings, they are not needed when referring to data objects or function names.

There is a short cut for help,

? shows the help page on a function name, same as help(function)

?read.table

?? searches for help pages on functions, same as help.search(‘phrase’)

??“t test”

Information is usually returned from a function, by default this is printed to screen

read.table(‘data.tsv’)

This can always be stored, we call what it is stored in an ‘object’

mydata

here mydata is an object of type dataframe

Reminder:

Vector: a list of numbers, equivalent to a column in a table
Data Frame = a collection of vectors. Equivalent to a table

Hint:

Up/Down arrow keys can be use to cycle through previous commands

OpenCPU

Rahul Nayak — Sun, 05 Jul 2015 18:34:46 -0500

OpenCPU is a system for embedded scientific computing and reproducible research. The OpenCPU server provides a reliable and interoperable HTTP API for data analysis based on R.

The OpenCPU JavaScript client library provides the most seamless integration of R and JavaScript available today.

OpenCPU uses standard R packaging to develop, ship and deploy web applications. Several open source example apps are available from Github.

Installing your own OpenCPU server is super easy and only takes a few minutes.

More at https://www.opencpu.org/

CrossMap

Jitendra Narayan — Mon, 08 Feb 2016 15:47:00 -0600

CrossMap is a program for convenient conversion of genome coordinates (or annotation files) between different assemblies (such as Human hg18 (NCBI36) <> hg19 (GRCh37), Mouse mm9 (MGSCv37) <> mm10 (GRCm38)).

It supports most commonly used file formats including SAM/BAM, Wiggle/BigWig, BED, GFF/GTF, VCF.

CrossMap is designed to liftover genome coordinates between assemblies. It’s not a program for aligning sequences to reference genome.

We do not recommend using CrossMap to convert genome coordinates between species.

More at http://crossmap.sourceforge.net/

Address of the bookmark: http://crossmap.sourceforge.net/

IBL laboratory

Mon, 12 Aug 2013 02:02:29 -0500

The IBL laboratory focuses on the multi-disciplinary analyses of the global responses of model microorganisms, cyanobacteria (mainly Synechocystis PCC6803) and yeasts (mainly Saccharomyces cerevisae) to environmental stresses triggered by oxidative agents, heavy metals, or drastic changes in nutrients availability. The genome-wide responses studied with the "omics" techniques (transcriptomics, proteomics, metabolomics and genetics) generate a wealth of experimental data, which are processed, archived, integrated and represented as working models through bioinformatics and mathematics.

Link : http://www-dsv.cea.fr/en/instituts/institut-de-biologie-et-de-technologies-de-saclay-ibitec-s/unites-de-recherche/service-de-biologie-integrative-et-genetique-moleculaire-sbigem/laboratoire-de-biologie-integrative-lbi/presentation__1

Yau Group

Tue, 15 Oct 2013 13:05:15 -0500

Yau Group are a new research group based at the Wellcome Trust Centre for Human Genetics and the Department of Statistics at the University of Oxford.

Yau Group develops statistical and computational methods for the analysis of genomic datasets with a particular interest in cancer sequencing applications and the use of Bayesian Statistics.

Yau Group are currently have projects in somatic mutation analysis of heterogeneous cancers, data fusion or integration techniques and single cell genomics.

More @ http://www.well.ox.ac.uk/~cyau/index.html

MATHomics Lab

Tue, 19 Nov 2013 18:17:32 -0600

Mathomics is a collaborative research group of the Center for Mathematical Modeling and the Center for Genome Regulation at University of Chile, created to play a central role in the development of biotechnological projects, providing state of the art bioinformatics and mathematical modeling tools, allowing to face these problems from the point of view of Systems Biology.

Lab page @ http://www.mathomics.cl/

BOKU Lab

Wed, 08 Jan 2014 19:33:12 -0600

We are interested in the study of complex systems in living organisms. Novel views augmenting the classical gene by gene approaches are required to overcome the engineered redundancies and combinatorial effects prevalent in higher eukaryotes. We therefore combine work to establish improved quantitative experimental assays, such as microarrays or differential in-gel electrophoresis, and development of modern computational methods, such as hierarchical probabilistic models or integration of heterogeneous data sources, focussed by biological studies in our laboratory and collaborations.

Highlights of our research include:

Optimization of microarray design, probe signal interpretation
Advanced models and tools for expression profiling
State-of-the-art applications and integrated analyses

Lab page @ http://bioinf.boku.ac.at/