Address of the bookmark: http://www.programmingr.com/category/stype/r-job-listings/

The only input requierement for UPhO is a tree (or trees) in Newick format in which the leaves are named with a species idenfifier, a field separator, and sequence identifier. By default, the field separator is the character "|" but custom delimiters can be defined. Examples of trees to test UPhO are provided in the TestData folder.

Address of the bookmark: https://github.com/ballesterus/UPhO

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

Following are the weblink for different available browsers:

http://www.ensembl.org/index.html

http://ensemblgenomes.org/

http://genome.ucsc.edu/

http://www.ncbi.nlm.nih.gov/genome

http://www.ebi.ac.uk/genomes/

http://flybase.org/

http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi

http://www.sanger.ac.uk/resources/databases/

This script has been modified by others to convert InDels as well, e.g. this by David Eccles

./vcf2fq.pl -f <input.fasta> <all-site.vcf> > <output.fastq>

https://github.com/gringer/bioinfscripts/blob/master/vcf2fq.pl

https://github.com/lh3/samtools/blob/master/bcftools/vcfutils.pl

The OpenCPU JavaScript client library provides the most seamless integration of R and JavaScript available today.

OpenCPU uses standard R packaging to develop, ship and deploy web applications. Several open source example apps are available from Github.

Installing your own OpenCPU server is super easy and only takes a few minutes.

More at https://www.opencpu.org/

1. FASTA
2. FASTQ
3. SAM
4. BAM
5. VCF
6. GFF
7. GTF

Address of the bookmark: https://bioinformatics.uconn.edu/resources-and-events/tutorials/file-formats-tutorial/

'du' – Check the size of a directory

$ du
This command ( du) gives you a list of directories that exist in the current working directory along with their sizes in kilobytes (default). The last line of the output gives you the total size of the current directory including its subdirectories.

$ du /home/jin1
The above command would give you the directory size of the directory /home/david

$ du -h
The same “du”command with some flag gives you a better output than the default one. The option '-h' stands for human readable format. Therefore, in order to print the sizes of the files / directories in your desire notation use this time suffixed with a 'k' if its kilobytes and 'M' if its Megabytes and 'G' if its Gigabytes.

$ du -ah
If you are interested in checking everything present in a folder use above mentioned command. It gives us not only the directories but also all the files that are present in the current directory. The “-a” flag displays the filenames along with the directory names in the output.

$ du -c
This gives you a grand total as the last line of the output. So if your directory occupies 30MB the last 2 lines of the output would be 30M.

$ du -s
Use this command to displays a summary of the directory size. It is the simplest way to know the total size of the current directory.

$ du -S
This would display the size of the current directory excluding the size of the subdirectories that exist within that directory. So it basically shows you the total size of all the files that exist in the current directory.

$ du --exculde=mp3
Several times it required to exclude some directory in our size calculation. In such cases the above command would display the size of the current directory along with all its subdirectories, but it would exclude all the files having the given pattern present in their filenames.

'df' - finding the disk free space / disk usage

$ df
Hmmm … now “df” command is really useful, and I guess you are going to use it over time. Typing the above command, outputs a table consisting of 6 columns. All the columns are very easy to understand. Remember that the 'Size', 'Used' and 'Avail' columns use kilobytes as the unit. The 'Use%' column shows the usage as a percentage which is also very useful.

$ df -h
Displays the same output as the previous command but the '-h' indicates human readable format. Hence instead of kilobytes as the unit the output would have 'M' for Megabytes and 'G' for Gigabytes.

Example: Linux installed on /dev/hda1
$ df -h | grep /dev/hda1

All right, this is not the only option to check the sizes and free spaces but there are a few more options that can be used with 'du' and 'df' . I will discuss it later.

Genome assembly projects typically run multiple algorithms in an attempt to find the single best assembly, although those assemblies often have complementary, if untapped, strengths and weaknesses. We present our metassembler algorithm that merges multiple assemblies of a genome into a single superior sequence. 

Address of the bookmark: https://sourceforge.net/projects/metassembler/?source=directory

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.