Finding Duplicated articles

sudo apt-get install fslint

http://www.pixelbeat.org/fslint/

 

How to test speed from internet using the command line ?

git clone https://github.com/sivel/speedtest-cli
cd speedtest-cli
python2.7 speedtest-cli

Source:http://stackoverflow.com/questions/426272/how-to-test-internet-connection-speed-from-command-line

Works like a charm!

 

Links da Semana

http://jakevdp.github.com/blog/2013/01/03/will-scientists-ever-move-to-python-3/

http://www.rna-seqblog.com/information/next-generation-sequencing-vs-microarrays/

http://www.homolog.us/blogs/2013/01/18/personal-genomics-the-ultimate-privacy-killer/

http://ivory.idyll.org/blog/why-i-blog-2013-version.html

http://www.rna-seqblog.com/data-analysis/bioinformatics-next-gen-sequencing-virtual-issue/

http://www.homolog.us/blogs/2013/01/18/a-quick-update-on-what-we-are-up-to/

http://blogs.plos.org/dnascience/2012/11/01/why-i-dont-want-to-know-my-genome-sequence/

http://mendeliandisorder.blogspot.com.br/2012/02/sequencing-my-exome-why.html

http://mendeliandisorder.blogspot.sg/2012/11/why-i-dont-want-to-know-my-genome.html

http://www.rna-seqblog.com/information/next-generation-sequencing-vs-microarrays/

 

How to create a unity launcher

https://help.ubuntu.com/community/UnityLaunchersAndDesktopFiles

 

Instalando Postgresql no Ubuntu 12.04

sudo apt-get purge postgresql-9.1
sudo apt-get purge postgresql-9.1*
sudo apt-get purge postgresql-8.4
sudo apt-get purge postgresql-8.4*
sudo apt-get install postgresql-9.1
sudo apt-get install postgresql-client-9.1

Sources:

http://ubuntuforums.org/showthread.php?t=1862358

https://help.ubuntu.com/community/PostgreSQL

http://www.cyberciti.biz/faq/howto-add-postgresql-user-account/

 

How to partition your computer for windows and linux?

This kind of partition configuration let me always have windows and linux at the same time and I can format linux at any time without changing anything on my /home

Device Boot      Start         End      Blocks   Id  System

/dev/sda1   *        2048      409599      203776    7  HPFS/NTFS/exFAT
/dev/sda2          409600   226192803   112891602    7  HPFS/NTFS/exFAT
/dev/sda3       616818688   625140399     4160856    c  W95 FAT32 (LBA)
/dev/sda4       226193406   616818687   195312641    5  Extended
/dev/sda5       226193408   265253954    19530273+  83  Linux
/dev/sda6       265256960   275019775     4881408   82  Linux swap / Solaris
/dev/sda7       275021824   616818687   170898432   83  Linux

 

 

Broad releases FASTG reference format that contains variation

The FASTG Format Specification Working Group is pleased to announce version 1.0 of the FASTG specification

FASTG is a format for faithfully representing genome assemblies in the face of allelic polymorphism and assembly uncertainty. Currently genome assemblies are represented linearly, as sequences of bases, recorded in FASTA files. Since chromosomes are in fact linear or circular, this makes sense, so long as one has complete knowledge of the genome. However, many genomes contain polymorphisms that cannot be represented in a simple linear sequence, and almost all assemblies contain errors and omissions, which can result in incorrect biological inferences. The FASTG format aims to address this problem using a flexible graph-based approach to encode any variability in the sequence, along with metadata to score and annotate the source of those variations. Assembly graphs in FASTG can be easily translated into linear FASTA sequences to support current analysis tools for reading mapping, annotation, visualization, etc, but our hope is to develop a next generation of assembly and genome analysis algorithms that can work with the graph structure directly. For the complete specification and additional information on FASTG, please visit:

http://fastg.sourceforge.net

http://fastg.sourceforge.net/FASTG_Spec_v1.00.pdf

If you are interested to discuss this further, please subscribe to the assemblathon-file-format mailing list:

http://assemblathon.org/pages/mailing-list

The immediate plans are to enlist help to develop a reference library and command line suite for parsing, transforming, and querying assemblies in FASTG format, similar to the widely used SAM/SAMTools suite.

source: http://www.biostars.org/p/59370/

 

Your Genome? Which One?

One thing is clear at this stage: the assumption that each individual has a unique genome has been overthrown to some extent. Think how this might impact common evolutionary studies. For years, evolutionists have claimed small differences between human and chimpanzee genomes. What if the percent difference is a function of the source cells used? Remember, the Yale team found differences between cells in the same organ — human skin. If the percent difference grows or shrinks depending on the source, any conclusions about human-chimp similarities would prove unreliable.

 

It’s also not clear yet whether geneticists will be able to mask the differences between cells to establish an individual’s genome (to say nothing of a species’s genome) as a useful concept. Results would appear to be a function of investigator choice. Say, for instance, that an evolutionist chooses to compare genes of a particular kind of blood cell between species. If the CNV’s and SNP’s vary significantly from blood cell to blood cell within the individual, the results will be skewed. Mixing or averaging the maps of numerous cells, though, risks creating a theoretical construct that does not correspond to reality. Which cells should be averaged? Will the averages converge or diverge, depending on which cells are selected? Philosophers of science can have fun with this one.

Claims about evolutionary similarities and differences based on genetics must be taken with a grain of salt from now on. Perhaps the feared “profound implications” will prove inconsequential. If nothing else, though, the Yale study provides an example of conceptual superstructures built on shaky assumptions and “prevailing wisdom.” As those of us in the intelligent design community know, what prevails at a given moment is not necessarily wise.

 

Source:http://www.evolutionnews.org/2012/11/your_genome_whi066601.html

 

50 tons de cinza

50 tons de cinza:

require(ggplot2)
grey50 <- data.frame(
x = rep(1:10, 5),
y = rep(1:5, each=10),
c = unlist(lapply(seq(10,255,5), FUN=function(x) { rgb(x,x,x, max=255) })),
t = unlist(lapply(seq(10,255,5), FUN=function(x) { ifelse(x > 255/2, 'black', 'white') }))
)
ggplot(grey50, aes(x=x, y=y, fill=c, label=c, color=t)) + 
geom_tile() + geom_text(size=4) +
scale_fill_identity() + scale_color_identity() + ylab(NULL) + xlab(NULL) + 
theme(axis.ticks=element_blank(), axis.text=element_blank())

 

Daily Reports

Availability – miRGator v3.0 update is available at: http://mirgator.kobic.re.kr
Cho S, Jang I, Jun Y, Yoon S, Ko M, Kwon Y, Choi I, Jang H, Ryu D, Lee B, Kim VN, Kim W, Lee S. (2012) miRGator v3.0: a microRNA portal for deep sequencing, expression profiling and mRNA targeting. Nucleic Acids Res

http://www.rna-seqblog.com/data-analysis/databases/mirgator-v3-0-a-microrna-portal-for-deep-sequencing-expression-profiling-and-mrna-targeting/

Computational thinking in the era of big data biology
Schatz MC
Genome Biology 2012, 13:177 (29 November 2012)
http://genomebiology.com/2012/13/11/177

http://www.ihid.co.uk/blog/why-doctors-should-learn-to-code

Genome interpretation and assembly—recent progress and next steps

http://www.nature.com/nbt/journal/v30/n11/full/nbt.2425.html