http://search.cpan.org/~lds/Bio-Graphics-2.37/

Address of the bookmark: http://search.cpan.org/~lds/Bio-Graphics-2.37/

Install latest Perl (with supporting multithreading) and CPANMinus.

 $ cd
 $ git clone git://github.com/tokuhirom/plenv.git ~/.plenv
 $ git clone git://github.com/tokuhirom/Perl-Build.git ~/.plenv/plugins/perl-build/
 $ echo 'export PATH="$HOME/.plenv/bin:$PATH"' >> ~/.bashrc
 $ echo 'eval "$(plenv init -)"' >> ~/.bashrc
 $ source ~/.bashrc
 $ plenv install 5.18.1 -Dusethreads
 $ plenv rehash
 $ plenv global 5.18.1
 $ plenv install-cpanm

• git is a distributed revision control and source code management software which can help you to download files from GitHub server.
• echo means "print".
• >> means adding the output into the end of the file, while > means adding the output by overwriting the whole file. Please use> with additional cares.
• In Linux system, there are two types of outputs when you execute a command. One is called standard output (or sometimes STDOUT for short), and the other is a standard error (STDERR). 1> is for STDOUT only, 2> is for STDERR only, and &>means for both. In default > is the same to 1>.
• exec is execution.
• Remember to install Perl in supporting multithreading (with option -Dusethreads), which is important for many NGS analysis packages (e.g. Trinity). In this setting, you can use multiple CPU for Perl software.
• Install the CPAN (Comprehensive Perl Archive Network) manager software, CPANMinus, by install-cpanm.

You can use plenv global and plenv local to change the different version of Perl to fulfil different needs of your Perl software.

For example, if the specific version of Perl is not compatible with your script, you can switch to the different version by:

 $ plenv local 

• It is similar to set the local version of your script language when you use pyenv and rbenv as the following.

Put the following path into ~/.bashrc file.

export PERL5LIB="$HOME/.plenv/build/perl-5.18.1/lib"

Install BioPerl and PerlIO::gzip

CPANMinus is a very good Perl module manager, use cpanm to install BioPerl can save you a lot of time. Here are some useful modules:

$ cpanm Bio::Perl
$ cpanm Bio::SearchIO
$ cpanm PerlIO::gzip

For more information, please visit: https://github.com/tokuhirom/plenv

This is the simple way to use the module

Example1:

use Benchmark;

$first_time = Benchmark->new;

our code……

$second_time = Benchmark->new;

$final_difference = timediff($first_time,$second_time);

print “the code took, timestr($final_difference),”\n”;

that was a very simple way to know the time diff , we can use it to know the time taken by some part of the code in the program.

More sophisticated way:

use Benchmark;
sub first {

my(arguments) = @_;

}

timethese(100, { first => ‘first_sub(arguments)’});

The first argument to timethese is 100 (evaluate 100 times).

Hope this very small tutorial with Benchmark will help people get started.

If you're interested in refreshing your memory or just new to the series, please check previous entries over here: 1 2 3

https://metacpan.org/pod/AI::MXNet

Address of the bookmark: http://blogs.perl.org/users/sergey_kolychev/2018/07/machine-learning-in-perl-kyuubi-goes-to-a-modelzoo-during-the-starry-night.html

Alternatively, use one liner perl script:

perl -ne 'if(/^>(\S+)/){$c=$i{$1}}$c?print:chomp;$i{$_}=1 if @ARGV' GIs.txt >sequence.fasta

where GIs.txt contains a list of GIs or accession IDs.

(from :http://edwards.sdsu.edu/labsite/index.php/robert?start=5)

Address of the bookmark: http://edwards.sdsu.edu/labsite/index.php/robert/380-ncbi-sequence-or-fasta-batch-download-using-entrez

https://github.com/IGS/twinblast

https://mra.asm.org/content/8/35/e00842-19

Address of the bookmark: https://github.com/IGS/twinblast

1. Learn and get updated

Some of the bad biological programmers only learn new technical or non-technical things when it’s absolutely necessary. The good biological programmers learn new technical skills proactively. But great biological programmers not only learn new technical skills on their own but also learn non-technical skills, and have an open mind to sources of knowledge that others may shut out.

In other concrete term, the bad biological programmer learn Perl's regular expression when they started a project on comparative genomics; the good biological programmer learned it a year before because it looked interesting; and the great biological programmer also read about the BioPerl packages, genomics, DNA string, genomic theories, or some similar course of study so that they could understand the results and explain it biologically.

2. Not a merely coder!!!

I often encountered with biological programmer who call themself a hard-core computer programmer and avoid biology. I can almost guarantee that if you are one of them then you are not doing research but merely writing "dry" codes.

According to my supervisor most of the computational biologist, don't know what they are doing biologically. Even they struggle to explain their own programs output and results. Therefore, It is highly advisable to learn basic of biology which can assist you to explain the result and understand your discovery. Always remember you are a researcher not a coder.

3. Be Social with biologist

The computational biologist spends most of the time in from of computers, writing codes. They always think their job is to produce working codes, not technical research perfections. But, they are completely wrong. You should not forget that apart from your computational skills you also need some biologist, other than your supervisor, to explain and make you understand the complex biological mechanism.

I highly recommend your to interact with biotech researchers and learn how do they explain their one graph (which they generally produce after one year of work) biologically. Remember, the origin of your research project is complex biological phenomenon, which is more complex than that of your limited programming rules.

4. Do not search, research for answers

Researching for answers means more than typing several keywords into a search engine or posting a question at Stack Overflow or the BioStars forums. I have entered problems into search engines that generate no results, and every question I posted on Stack Overflow or the BioStars forums never got anything resembling an answer, yet I solved the issues and moved on. I’m not a magician — I just know how to find answers or discover root causes.

Many problems are situational, and if you depend on search engines and forums, you can waste a lot of time going down a rabbit hole and possibly never getting a solution. Learn to perform root cause analysis, learn enough about the underlying system to look for other clues and solutions, and learn to take a long distance view of an issue before deep diving into it.

5. Love and defend your research

You cannot rise to the top in this research profession without loving your work. There are some very good “it’s just a job” biological programmers (I’ve been one at times), but if that is your outlook, you won’t be willing to do whatever it takes to succeed. This idea gets a lot of folks in a huff, because they feel it is a personal insult. “I’m a good programmer, but I have other priorities and can’t make work my life.” I understand completely; I have other priorities too. As much as I hate to say it, when I am passionate about my work, I am willing (though not eager) to abandon my other priorities to finish the job. It is not an insult to say that if you aren’t willing to pull out all the stops you can’t be the best, it is a fact.

You must be passionate about more than programming — you must also be excited about your research, the tools and technology you are using, and so on. I have seen very good and even great biological programmers operating at mediocre levels because something was not a good fit, such as they hated the project or were using a technology they disliked. Therefore, like your research project and get excited about your discoveries. You have not only to discover but also defend your finding with scientific words.

Thanks to all of you for reading.

http://ritg.med.harvard.edu/training/perl/RC_Perl_Intro.pdf