Tag Archives: NGS

RNA-Seq bioinformatics analysis video tutorial

I often spend some time on Rafael Irizzarry’s youtube channel, that is provided with very useful and clear video tutorials and insights on bioinformatics and statistics. In this video- tutorial, a farily explanatory introduction to RNA- Seq data analysis is perfromed by Kasper Hansen, who gives an introduction to RNAseq and relevant computational and statistical issues. The tutorial starts explaining the RNA-Seq technical basics, to go further with an insight of the statistical methods of data analysis and some good tip on how to conduct your RNA-Seq analysis routine.

I am making a big use of this, since I am improving my RNA-Seq analysis skills at the moment, and I really hope and think that you will enjoy this talk as I did.

NGS and data analysis for epigenetics. A couple of reviews to take stock of the situation.

Epigenetic regulation of DNA is a point of growing interest. If many evidences lead to the idea that genotype and phenotype are linked in a very complex relationship, the genome architecture is the main player in this puzzling game affecting gene frequencies. Both 3D arrangement of chromatin, and the disposition of nucleosomes along the DNA, have been found to affect genomic regulation, and to have a crucial importance in evolution, adaptation, disease etiology and possible therapeutic approaches. Facing this complexity is a big challenge, and the best weapon we can use to afford it is high- throughput methods and Next- Generation Sequencing. I was focusing on this in the last days, and have found a couple of good reviews to understand the state of the art: NGS, in epigenetics, planet Earth, year 2014.

Epigenetics: an updated overview

If you are looking for a good and updated overview of what epigenetic is, and a good summary of the main topics, I can definitely suggest this paper. Authored by Shrutii Sarda and Sridhar Hannenhalli, bioinformaticians at the University of Maryland, the paper summarizes in a very brief, but still really clear overview, “the various types of epigenomic data afforded by NGS, and some of the novel discoveries yielded by the epigenomics projects” (cit.). In a few words: what is epigenomics, how to do it, and why it worths a try.

NGS: one achronym, many techniques

The NGS technologies are a set of experimental algorithms, implemented by different corporations into several commercial solutions. A discussion on wich solution fits better in a specific experimental need could be quite long to be properly made, and very often the choice of a specific machine is determined by the availability of the lab and the project specific needs, and influenced by the personal preference of the researcher. Anyways, here we go with some papers to get a fairly good overview of the main techniques.

A comparison of NGS Systems is the topic of a paper published by Linda Liu at the Beijing Genomics Institute, and available in PDF on atcgeek. After telling briefly the story of nucleic acids sequencing, the authors compare in detail all the features of Roche 454, AB Solid, Illumina GA and Compact PGM systems.

Talking about epigenomics, we can’t help focusing on Chip-Seq in particular. The most recent and best explanatory review about Chip-seq I got to find has been published on Nature in 2012. Authored by Terence Furey, chromatin structure expert at North Carolina University, the article reports the main methods to detect and functionally characterize DNA-bound proteins, starting from Chip-seq, but still going beyond.

The possible applications are countless, ranging from evolutionary biology to biomedicine, and I think it would be quite pointless spending further words on this. This post aims to give some little tip to those guys that are approaching massive sequencing and epigenomics for the first time, or to those one that need to keep up to date in this.

A world map of High- Throughput Sequencers.

Just a quick post to report a small but really interesting project I found sifting through the Internet. Since a few years, the web is filling up with maps of different types. In the semantics of contemporary web language, maps represent the most chosen way to describe global- sized phenomena, and the development of new interactive and customizable maps software is enhancing up this trend. I would say that this “map mania” is affecting genomics too, but it wouldn’t make much sense, since genetics and genomics were already really familiar with maps years before any web trend. Anyways, if you already could find a map of the best places to pick up a girl in the world, or a map indicating the most paid job in any single US State, now you can also check the world wide distribution of NGS technologies. Omicsmaps.com shows a very detailed world map of High- throughput Sequencers. You can search through the institutes hosting an NGS by sequencer category (5, HiSeq, Illumina GA2…), jump directly to a chosen country and report the ones you know and are missing.

Just a couple of updates. I am writing my thesis, so this blog will slow down till winter holidays. I really would like to mention how looks depressing to me the NGS map of Italy, but I will save you from my complaints. Anyways, I am working on a post to explain the situation of research and knowledge politics in Italy. I am also working on the podcast and it will be ready in a couple of weeks. Stay tuned. Or better: PLEASE, try to stay as tuned as you can.

Biotech Corporations: Illumina announces NextBio acquisition.

I republish almost on real time the announcement of one of the biggest transactions in the biotech corporate world in 2013. Right about three minutes ago, the headquarters of Illumina announced the acquiring of NextBio, leader in the field of biological BigData services. Illumina, founded in 1998 and accounted for more than 300 millions dollars of revenue, will define the acquisition within the end of October. It follows the official post from Illumina website.

SAN DIEGO–(BUSINESS WIRE)–Oct. 28, 2013– Illumina, Inc. (NASDAQ:ILMN) today announced it has signed a definitive agreement to acquire Santa Clara-based NextBio, a leader in clinical and genomic informatics. NextBio’s powerful big-data platforms aggregate and analyze large quantities of phenotypic and genomic data for research and clinical applications. With the addition of NextBio’s platform upon completion of the acquisition, Illumina will be able to offer customers enterprise level bioinformatics solutions that accelerate the discovery of new associations between the human genome and disease, and ultimately, enable the application of those discoveries within healthcare.

“This agreement with NextBio demonstrates Illumina’s unwavering commitment to drive the adoption of sequencing in new markets and vastly improve the genomic information workflow,” said Jay Flatley, President and CEO of Illumina. “NextBio enables the classification and aggregation of phenotypic and clinical data within a single environment and allows analysis of that data at unprecedented speed and scale. The combination of Illumina’s BaseSpace cloud computing environment for next-generation sequencing with NextBio’s platform for integrating patient data will allow us to deliver solutions that seamlessly integrate the entire workflow from sample to result.”

NextBio’s platform allows customers to quickly compare their experimental results against thousands of published and private data sets by means of a unique correlation engine, which pre-computes billions of significant connections between disparate data elements and helps discover new associations. NextBio Clinical, which in 2012 passed an independent HIPAA audit, is designed for seamless integration with existing clinical and research systems. Backed by highly scalable Software as a Service (SaaS) enterprise technology, it is capable of analyzing petabytes of data.

NextBio’s database platforms are currently used by researchers and clinicians in more than 50 commercial and academic institutions. NextBio will be integrated into Illumina’s newly formed Enterprise Informatics business under the leadership of Nick Naclerio, SVP of Corporate and Venture Development and General Manager ofEnterprise Informatics. NextBio co-founder Ilya Kupershmidt and Chief Technology Officer Satnam Alag will continue to provide scientific and technical leadership as part of the new business unit.

Illumina is confirming its 2013 financial guidance provided on October 21, 2013. The transaction is expected to close by the end of October.

Original article:  http://investor.illumina.com/phoenix.zhtml?c=121127&p=irol-newsArticle&ID=1869001&highlight=

Is Whole Genome Sequencing more performing than classical Genotyping?

Ask a german researcher and he may answer “yes, it is”, expecially if the german researcher you question is Stefan Niemann from the Molecular Mycobacteriology Department of the Forschungszentrum Borstel Institute in Sülfeld, Germany. Niemann’s team primary aim was to find a SNP-based distinction able to classify different Mycobacterium tuberculosis strains.  They considered 86 different strains of M. tuberculosis isolated from a TB outbreak in the german lander of Hamburg and Schleswig-Holstein in a period between 1997 and 2010, in wich more than 2000 people were affected by tubercolosis. They compared the classical genotyping, a standard test in matter of different strains classification,  with a whole genomic sequencing- based approach. This new test was found to provide more accurate informations on clustering and longitudinal spread of the patogen than the classical genotiping standard test. It is important to say that the whole genome sequencing revealed many falsely cludered by classical gentyping.

The whole genome sequencing let the authors estimate that the genetic material of M. tuberculosis evolved at a 0.4 mutations rate per genome per year, suggesting that the bacterium grows in infected people with a doubling time of 22 hours and 400 generations per year.

This article is a good proof of the potential of bioinformatics and new sequencing approaches. These methods provide more accurate information, can be applied in several fields of biological research and their cost is progressively decreasing. We can say that there is a good probability that these methods can become the new standards surpassing the classical genomics methods.

The authors of the article seem to believe this too: “Our study demonstrates that whole genome sequencing-based typing provides epidemiologically relevant resolution of large, longitudinal (Mycobacterium tuberculosis) outbreaks much more efficiently than classical genotyping. (…) We envision that (whole genome sequencing) progressive effective implementation will be accelerated by the continuously decreasing sequencing costs, broader distribution of so-called bench top genome sequencers, and upcoming bioinformatics developments to facilitate quick and relevant interpretation of the resulting data in public health and medical contexts.”

Source: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0039855