It is possible to create a vector by typing data directly into R using the combine function ‘c’

x

same as

x

creates the vector x with the numbers between 1 and 5.

You can see what is in an object at any time by typing its name;

x

will produce the output ‘[1] 1 2 3 4 5′

Note that names need to be quoted

daysofweek ← c(‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’);

Usually however you want to input from a file. We have touched on the ‘read.table’ function already.

mydata

Now mydata is a data frame with multiple vectors

each vector can be identified by the default syntax

#if any of these are typed it will print to screen

mydata$V1 mydata$V2 mydata$V3

By default the function assumes certain things from the file

• The file is a plain text file (there are function to read excel files: not covered here)
• columns are separated by any number of tabs or spaces
• there is the same number of data points in each column
• there is no header row (labels for the columns)
• there is no column with names for the rows** [I’ll explain].

If any of these are false, we need to tell that to the function

If it has a header column

mydata header=T also works

Note that there is a comma between different parts of the functions arguments

If there is one less column in the header row, then R assumes that the 1^st column of data after the header are the row names

Now the vectors (columns) are identified by their name

#if any of these are typed it will print to screen

mydata$A mydata$B mydata$C

# Summary about the whole data frame

summary(mydata)

# Summary information of column A

summary(mydata$A)

We can shortcut having to type the data frame each time by attaching it

attach(mydata)

# summary of column B as ‘mydata’ is attached

summary(B)

Two other important options for read.table

If is is separated only by tabs and has a header

mydata

Really useful if you have spaces in the contents of some columns, so R does not mess up reading the columns . However if the columns or of an uneven length it will tell you.

If you know that the file has uneven columns

mydata

This causes R to fill empty spaces in a columns with ‘NA’ .

The last two examples will still work with our file and give the same result as with only headers=T

Graphs

to get an idea of what R is capable of type

demo(graphics)

steps through the examples, and the code is printed to the screen

We will work with simpler examples that have immediate use to biologists.

Remember to get more information about the options to a function type ‘?function’

Histogram of A

hist(mydata$A)

If there was more data we could increase the number of vertical columns with the option, breaks=50 (or another relevant number).

boxplot(mydata)

We can get rid of the need to type the data frame each time by using the attach function

# if not already done so

attach(mydata)

boxplot(mydata$A, mydata$B, name=c(“Value A”, “Value B”) , ylab=“Count of Something”)

same as

boxplot(A, B, name=c(“Value A”, “Value B”) , ylab=“Count of Something”)

Scatter plot

# if not already done so

attach(mydata)

plot(A,B) # or plot(mydata$A, mydata$B)

SAVING an image

Windows users (Rgui) RIGHT click on image and select which you want.

These instructions work for everyone.

You need to create a new device of the type of file you need, then send the data to that device

to save as a png file (easy to load into the likes of powerpoint, also great for web applications.

png(‘filename’)

boxplot(A, B, name=c(“Value A”, “Value B”) , ylab=“Count of Something”)

or to save as a pdf

pdf(‘filename’)

boxplot(A, B, name=c(“Value A”, “Value B”) , ylab=“Count of Something”)

Note

• Nothing will appear on screen, the output is going to the file
• Also it may not be saved immediately but will once the device (or R) is turned quit.

To quit R type

q() # If you save your session, next time you start R, you will have your data preloaded.

Or if you want to remain in R

dev.off() #turns of the png (or pdf etc) device, thus forces the data to save

A postdoctoral training position is currently available in the Computational and Statistical Genomics Branch (CSGB) of the National Human Genome Research Institute (NHGRI). The position is located in the laboratory of Andy Baxevanis, Ph.D., whose research group uses comparative genomics approaches to better-understand the molecular innovations that drove the surge of diversity in early animal evolution. The overarching theme of Dr. Baxevanis’ research program is focused on how non-traditional animal models convey critical insights into human disease research.

Candidates should have or be close to obtaining a Ph.D. or equivalent degree in bioinformatics, computational biology, computer science, molecular biology, or a closely related field. Candidates with a background in evolutionary biology are particularly encouraged to apply. Programming skills and experience in the application of computational methods to genomic data are highly desirable. Applicants must possess good communication skills and be fluent in both spoken and written English. The ability to learn how to use new software and quickly become expert in its use, critical thinking, problem-solving abilities, and the ability to work semi-independently are required.
How to Apply

Interested applicants should submit a curriculum vitae, a detailed letter of interest, and the names of three potential referees to Dr. Baxevanis at andy@mail.nih.gov.
About Our Organization

The NIH Intramural Research Program is on the Bethesda, Maryland campus and offers a wide array of training opportunities for scientists early in their careers. The funding for this position is stable and offers the trainee wide latitude in the design and pursuit of their research project. The successful candidate will have access to NHGRI’s established and robust bioinformatics infrastructure, as well as resources made available through NIH’s Center for Information Technology (CIT) and the National Center for Biotechnology Information (NCBI).

For more information on CSGB and NHGRI’s Intramural Research Program, please see http://genome.gov/DIR/.

Bioinformatics Textbook Track

Find more about Rosalind puzzle at http://rosalind.info/problems/list-view/?location=bioinformatics-textbook-track

I will provide solution of all the Rosalind problem with Perl for community.

Check out the right sidebar for more links ...

A: He was getting too Sassy.

What did the bioinformatician say when he found out his team stopped using version control?

A: Y’all better Git!

Why did the computational biologist stay home from work?

A: He had a code!

Why was the bioinformatician's paper was rejected?

A: Journal thought it seemed scripted.

How can you tell that a Bioinformatics is working?

A: You can hear him Grunting!

Why bioinformatician always silence?

A: Because bioinformatician calmly whisper, “SSH”

Why was the bioinformatician always so sleepy?

A: He/She wasn’t given any Java.

Why did the program/software hanged?

A: Because genome float.

Why was the class upset that its parent died?

A: Because it wouldn’t be getting the inheritance!

Why did bioinformatician always works on the command line?

A: Because they don't want to scare you with huge amount of data!

Why did the bioinformatician attend the gay pride parade?

A: They supported polymorphism.

Why did bioinformatician prefer awk, PerlOneliner?

A: Because even computer can't handle to load the data.

Why don’t bioinformatician get along with others?

A: They’re too MEAN.

Why computational biologist are cool?

A: Because they are scripted!!

Why they talk $ unzip; strip; touch; finger; grep; mount; fsck; more; yes; fsck; fsck; umount; clean; sleep;

A: Ah, Ohhh, dude, these are *NIX commands

Did they really hack genome?

A: Yes, I guess so.

CDSA is pleased to announce a 4 days hands-on training program on “Essentials of Statistics and Data Analysis using R” at ICGEB, Aruna Asaf Ali Road, New Delhi on December 1 – 4, 2015. This will involve developing and enhancing skills to understand basic principles of statistics for summarizing data and use of appropriate statistical tests as well as providing an understanding of data analysis using R. Didactic lectures with practical sessions will be delivered by experienced faculties from AIIMS and Novartis. Live classroom with power point presentations, case studies, mock exercise, practical sessions on R, group work with time for discussion and Q&A sessions are added advantages of this workshop.

Please contact gayatrivishwakarma.cdsa@thsti.res.in or vineetabaloni.cdsa@thsti.res.in for program and registration details.

Please nominate personage or register yourself on or before November 6, 2015 along with the electronic transfer of registration fee.

Staff Scientists

Specialization: Applicant should have a Ph.D. with excellent academic credentials along with the track record of scientific productivity evidenced by publications/patents/products in the frontier areas of Plant Biology such as, Computational Biology, Genome Analysis and Molecular Mapping, Molecular Mechanism of Abiotic Stress Responses, Nutritional Genomics, Plant Development and Architecture, Plant Immunity, Molecular Breeding, Transgenics for crop improvement and other emerging areas based on plant genomics.

Remuneration: The length of experience and scientific accomplishments/quality of scientific productivity record will be major factors in deciding the level of appointment as Staff Scientist as well as starting salary in the Pay Bands of Rs 15,600-39,100 (with grade pay of 5400), and Rs 37,400-67,000 (with grade pay of 8,700 and 8,900) plus usual allowances admissible to the Central Government employees. However, NIPGR reserves the right to select candidates in the lower grade against the foregoing posts depending upon the qualifications and experience of the candidate. Reservation of posts shall be as per Govt. of India norms. Five posts (SC-2, ST-1, OBC-2) in the Pay Band of Rs 15,600-39,100 with Grade Pay of Rs 5400, are reserved.

More at http://www.nipgr.res.in/careers/vacancies_latest.php#

Apply online at http://www.nipgr.res.in/nipgr_recu/nipgr_recu.php

Form http://www.nipgr.res.in/files/careers/Application_Performa_2015.doc

Project Title : "Structural and functional characterization of serine biosynthetic pathway enzymes from Entamoeba histolytica"

No. of Post : 01

Qualification : Ph.D in any computational biology / bioinformatics

Desirable : 1. Experience with docking, simulations and structural biology with proof of publications is preferred. 2. National Eligibility Test cleared [CSIR/UGC] candidate is preferred.

Salary : According to CSIR rules
How to apply

The application on plain paper indicating name, date of birth/age, address, essential/technical/professional qualifications. experience, list of publications should reach The Prof. S. Gourinath, Principal Investigator, [Project Director], School of Life Sciences, Jawaharlal Nehru University, New Delhi-110067, on or before 23rd May 2016.

More at http://www.jnu.ac.in/Career/currentjobs.htm

A full-time post-doctoral position for a bioinformatician with experience in managing and analyzing NGS data is available in the Laboratory of Molecular Cardiology at Policlinico San Donato-IRCCS, Milan, Italy. For lab publications, see: http://scholar.google.it/citations?user=wAPKO9wAAAAJ&hl=it&oi=ao

https://www.researchgate.net/profile/Fabio_Martelli

The goal of the project is investigating the regulation and functional role of non coding RNAs in tissue response to hypoxia and ischemia.

We are looking for a candidate that is going to interact with biologists and bioinformaticians to manage and analyze NGS data (mostly RNA-seq) and microarray data.

The successful candidate must have a minimum of 3 years experience in dealing with NGS data, a good command of English and written communication and at least 2 relevant publications as first author in peer reviewed international journals. The candidate is expected to interact with a small international group and to be able also to work independently. Knowledge of programming is a definitive plus, as well as a good statistical background and/or wet molecular biology skills.

Salary is proportional to experience and to the publication record (up to 38 000euro/year before taxes and retirement contribution i.e. IRPEF and INPS).

Please, send your CV by e-mail to Fabio Martelli:

fabio.martelli@grupposandonato.it

Location: Laboratory of Molecular Cardiology at Policlinico San Donato-IRCCS, Milan, Italy.
Link: https://www.researchgate.net/profile/Fabio_Martelli
Contact person: Fabio Martelli
Contact email: fabio.martelli@grupposandonato.it

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.

More at http://cukerala.ac.in/index.php?option=com_content&view=article&id=1022:applications-invited-for-the-post-of-jrf-department-of-plant-science&catid=106&Itemid=593&lang=en