More at http://www.yandell-lab.org/software/maker.html

Address of the bookmark: http://www.yandell-lab.org/software/maker.html

More at https://github.com/aaronwolen/liftover

https://www.bioconductor.org/help/workflows/liftOver/

Address of the bookmark: https://github.com/aaronwolen/liftover

Address of the bookmark: http://marinetics.org/teaching/hts/Assembly.html

University of Ibadan (UIB)­Ibadan:
There has been significant increase in the number of bioinformatics activities in Nigeria (and West Africa) since 2003 when the program was initiated by the West African Biotechnology Workshops Series (WABWS, http://www.wabw.org) at the University of Ibadan, Nigeria (in collaboration with  the South African National Bioinformatics Institute (SANBI, http:/www.sanbi.ac.za). Workshops  that were open to scientists from all African countries have seen a very high number of applications  from scientists based in West Africa. The encouraging desire to acquire cutting­edge skills to  computational process data and extract useful knowledge from genome projects led to the interest of  the West African Biotechnology Workshops (WABW) to develop an agenda to address the  bioinformatics skills gap among scientists in West Africa. An increased commitment from agencies  like NEPAD would be required in the provision of infrastructure to establish and sustain regional  and national networks.

University of Ilorin (UIL)­Ilorin:
The University of Ilorin was established in 1976 by the Federal Government of Nigeria.  Bioinformatics activities started at the University in February 2003 with the establishment of the  West African Bioinformatics Research Initiative (WABRI). However, progress has been rather slow  due to inadequate funding. We are mainly engaged in Bioinformatics training at the introductory  level and proteomics studies on various species of malaria parasites. Recently, we became interested  in comparative genome analysis of various species of  Plasmodium  and the comparison of  chloroquine sensitive and chloroquine resistant strains of Plasmodium falciparum. Other activities  and areas of interest can be seen on our website, http://www.wabri.org, although not all our  proposed interests have been fully implemented due to our level of funding.

Training:
The University of Ilorin has introduced M.Sc. and Ph.D. programmes in Computer Science (with  options in Bioinformatics). The programme is based in the Department of Computer Science and  emphasis is on the development of algorithms to solve problems in bioinformatics. The Covenant University offers M.Sc. and Ph.D in Computer Science with option in Bioinformatics  (Computational Biology). Furthermore, through affiliated departments, the CBBM is been design to award Diploma and Degree certificates in Biotechnology.

Web sites and links: http://www.covenantuniversity.com http://www.run.edu.ng http://www.uniben.edu http://www.wabri.org http://www.wabw.org http://www.unilorin.edu.ng http://www.wabri.org http://www.asopah.org

To read more about this collaboration, visit: https://edu.t-bio.info/pine-biotech-joins-forces-with-the-bioclues-organization-to-promote-bioinformatics/

Pondicherry University Puducherry has been identified as a nodal agency by the Department of Biotechnology, Govt. of India to coordinate this examination along with nine centres namely, Pune University, Pune; Anna University, Chennai; Calcatta University (WBUT) Kolkata; Institute of Bioinformatics & Applied Biotechnology, Bangalore; North-Eastern Hill University, Shillong, University of Hyderabad, Hyderabad; University of Kerala, Thiruvananthapuram; Jawaharlal Nehru University, New Delhi and Assam Agricultural University, Guwahati.

In the BINC 2013 examination,17 candidates were certified. DBT has agreed to fund Research fellowships for all the BINC qualified Indian nationals to pursue Ph.D. in Indian Institutes/Universities. Note that the candidate must possess a postgraduate degree(or equivalent) & meet the criteria of the institutes/universities in order to avail research fellowship. In addition, cash prize of Rs. 10,000/- will be awarded to the top 10 BINC qualifiers.

More at http://210.212.230.224:9999/BINC/

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

#Find the reverse complement of a DNA string.
#Given: A DNA string Pattern.
#Return: Pattern, the reverse complement of Pattern.

use strict;
use warnings;

my $string="AAAACCCGGT";
my $finalString="";
my %hash = (
    "C" => "G",
    "A" => "T",
    "T" => "A",
    "G" => "C",
);

for (my $aa=0; $aa<=(length($string)-1); $aa++) {
    my $char=substr $string, $aa, 1;
    #print $hash{$char};
    $finalString="$hash{$char}"."$finalString";
}

print $finalString;
print "\n";