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

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/

• Function(data, options)

Even quit is a function

• q()

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

With InsideDNA, you can upload and store your own genomic/genetic datasets in a limitless cloud space, and instantly analyze it with a powerful compute instance, without any tool installation or set up hassle.

More at https://insidedna.me/

Address of the bookmark: https://insidedna.me/

Eligibility : MSc(Bio-Informatics), BE/B.Tech

Location : Kasaragod

Last Date : 20 Dec 2015

Hiring Process : Face to Face Interview
Central University of Kerala

JRF job opportunity in Central University of Kerala (CUK) on temporary basis

Project Title : "Targeting TAL effector mediated susceptibility for durable and broad-spectrum resistance to bacterial blight in Rice"

No. of Post : 01

Qualification : MSc in any subject under Life Science or Bioinformatics/ B.Tech in Bioinformatics + 1 yr experience

Stipend : Rs. 14,000/-
How to apply

Interested candidates are requested to send their applications explaining their interest in the position with an updated CV to Dr. Ginny Antony, Assistant Professor, Department of Plant Science, School of Biological Sciences, Central University of Kerala, Padannakkad, Kasaragod, Kerala - 671 314 email: ginnycuk2013@gmail.com on or before 20th December, 2015.

Eligibility : ME/M.Tech(Bio-Informatics/Bio-Chemistry Engg, CSE), MSc(Bio-Informatics, CS)

Location : Delhi

Last Date : 18 Dec 2015

Hiring Process : Walk - In
IARI - Job Details

JRF/Traineeship/Studentship Bioinformatics job position in Indian Agricultural Research Institute (IARI) purely temporary

JRF

Qualification: i) Master’s degree in Bioinformatics or Computer Science + NET qualification, or ii) M. Tech degree in Bioinformatics or Computer Science/Engineering

Desirable: Efficiency to handle agricultural databases and bioinformatics tool development

Pay Scale :Rs 25000/-

Age limit : 35 years

Traineeship/2 Post

Qualification: M.Sc./M. Tech (Bioinformatics) with 60 % marks from a recognized University

Pay Scale :Rs. 8000/-consolidated

Age limit : 35 years

Studentship/4 Post

Qualification: Final year M.Sc./ M.Tech (Bioinformatics) Students from a recognized University

Pay Scale :Rs. 8000/-consolidated

Age limit : 35 years
How to apply

Walk-in-Interview will be held on 18th December 2015 at 10:00 AM at AKMU, LBS Building,IARI, Pusa Campus, New Delhi-110012. Bring self attested copies and originals of all certificates ( class 10th )onwards along with biodata in the attached format, proof of date of birth, one passport size photo, NOC from present employer, if any.

More at http://www.iari.res.in/index.php?option=com_jumi&fileid=24&Itemid=664

Eligibility : ME/M.Tech(Bio-Informatics/Bio-Chemistry Engg), MSc(Bio-Informatics)

Location : Hyderabad

Last Date : 30 Dec 2015

Hiring Process : Written-test
University of Hyderabad

JRF Bioinformatics job position in University of Hyderabad

Project Entitled : Programming protective humoral responses with novel vaccine formulations against Dengue Virus

Essential Qualifications : M. Sc. in Life Sciences/Bioinformatics/ or M. Tech in Bioinformatics with a minimum of 60% marks and with CSIR-UGC JRF/NET or valid GATE score are preferred. Desirable : Candidates should have six months to one year hands on experience in molecular biology techniques like gene cloning, protein expression and purification, hands on various nano-formulations for drug/vaccine delivery, immunological assays including animal handling, immunizations, T cells and B cell assays or Candidate should have strong background in Bioinformatics and computational Biology, good programming skill particularly proficiency in R/PERL/PYTHON. Candidates interested in above position should send a one page statement clearly explaining how their skills are relevant to the above said position. The candidates should also enclose detailed CV and the name/Email IDs of three references

Fellowship : Rs. 16,000 p.m. + 30% H.R.A. for the first two years (Revised DBT fellowship guidelines maybe applicable)

Duration : The appointment will be on temporary basis for a period of one year. Based on performance, the appointment could be extended till the end of project

How to apply

Submit your application (hardcopy) in a closed envelope to Dr.Nooruddin
Khan, Room S-66B,Department of Biotechnology and Bioinfromatics, School of Life Sciences, University of Hyderabad, Gachibowli, Hyderabad 500 046 or E mail: nklabsls@gmail.com. Last date for receipt of applications is on or before 30.12.2015

More at http://uohyd.ac.in/index.php/component/content/article/87-administration/recruitments/129

https://www.pmgenomics.ca/hoffmanlab/

The Ensembl comparative genomics resources are one such reference set that facilitates comprehensive and reproducible analysis of chordate genome data. Ensembl computes pairwise and multiple whole-genome alignments from which large-scale synteny, per-base conservation scores and constrained elements are obtained. Gene alignments are used to define Ensembl Protein Families, GeneTrees and homologies for both protein-coding and non-coding RNA genes. These resources are updated frequently and have a consistent informatics infrastructure and data presentation across all supported species. Specialized web-based visualizations are also available including synteny displays, collapsible gene tree plots, a gene family locator and different alignment views. The Ensembl comparative genomics infrastructure is extensively reused for the analysis of non-vertebrate species by other projects including Ensembl Genomes and Gramene and much of the information here is relevant to these projects. The consistency of the annotation across species and the focus on vertebrates makes Ensembl an ideal system to perform and support vertebrate comparative genomic analyses. We use robust software and pipelines to produce reference comparative data and make it freely available.

Database URL: http://www.ensembl.org.

Address of the bookmark: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4761110/

More at http://busco.ezlab.org/

Address of the bookmark: http://busco.ezlab.org/