The fellowship will be for a period of 3 years, or for a period of 4 years, with 25 % compulsory work (e.g. teaching responsibilities at the department) contingent on the qualifications of the candidate and the teaching needs of the department.

Starting date no later than October 1, 2021.

More at https://www.jobbnorge.no/en/available-jobs/job/199984/phd-research-fellow-in-genomics-and-bioinformatics

Like other indel callers, Scalpel works by performing de novo assembly of regions of interest, so that misalignment to the reference genome cannot obscure the presence of an insertion or deletion. Scalpel's innovation is to repeatedly check its assembly before comparing to the reference genome, to account for simple sequence repeats that are a regular source of error in indel calling. When Scalpel assembles an exon, it collects reads that map to that exon (including partial matches), splits them into k-mers, and creates a de Bruijn graph to span the exon; however, if it detects repeats in the map, it iteratively increases the size of the k-mers by one base until the repeats are eliminated. This ensures that the final assembly of the exon is highly accurate while minimizing compute time.

The Cold Spring Harbor team's validation of Scalpel, published over the weekend in Nature Methods, compares Scalpel's performance on a live whole exome against HaplotypeCaller and SOAPindel. The donor is an individual with serious neurological disorders, which may be linked to a high incidence of indels. One thousand indels from this individual's exome, called by one or more of the informatics pipelines, were selected for focused resequencing. This resequencing revealed a 77% true positive rate for Scalpel calls, dramatically better than the rates for either of the competing tools; Scalpel performed especially well with indels longer than five base pairs, a traditional weak point for indel callers.

Finally, the authors demonstrate Scalpel's use on a large set of genetic data from nearly 600 families who donated samples to the Simons Simplex Collection, a project of the Simons Foundation Autism Research Initiative. Scalpel found a very high enrichment for indels in children affected by autism, compared with their unaffected siblings, a pattern that persisted even after excluding common variants.

More at sandbox.bio

Address of the bookmark: http://sandbox.bio

• In a GitHub or GitLab repository
• Free to use
• Written in markdown or similar

NOTE: This list of courses is selected only based on the above criteria.
There are no checks on quality.

https://glittr.org/?per_page=25&sort_by=stargazers&sort_direction=desc

Address of the bookmark: https://glittr.org/?per_page=25&sort_by=stargazers&sort_direction=desc

1. NCBI (National Center for Biotechnology Information):

   • NCBI provides various databases related to genetic information, including 16S rRNA sequences.
   • You can access the 16S ribosomal RNA sequences from NCBI's Nucleotide database (https://www.ncbi.nlm.nih.gov/nucleotide/).
   • Perform a search using keywords like "16S rRNA" or specific bacterial names to find relevant sequences.
   • You can download sequences individually or in batches using the provided tools.

2. GreenGenes:

   • GreenGenes is a widely used 16S rRNA gene sequence database.
   • You can access it at http://greengenes.secondgenome.com/.
   • GreenGenes provides precompiled databases for various purposes, including classification, alignment, and phylogenetic analysis.

3. SILVA:

   • SILVA (https://www.arb-silva.de/) is another comprehensive database for ribosomal RNA (rRNA) sequences.
   • It covers not only 16S rRNA but also other ribosomal RNA sequences.
   • SILVA provides precompiled databases for various purposes, including taxonomic classification and alignment.

4. Ribosomal Database Project (RDP):

   • RDP (http://rdp.cme.msu.edu/) is a curated database that offers 16S rRNA sequences.
   • It provides tools for sequence analysis and classification.
   • You can download sequences and taxonomy information from their website.

5. QIIME (Quantitative Insights Into Microbial Ecology):

   • QIIME (https://qiime2.org/) is a widely used bioinformatics platform for microbiome analysis.
   • It provides tools for analyzing microbial communities, including processing 16S rRNA sequences.
   • QIIME often includes its own preprocessed 16S rRNA databases that can be used for analysis within the platform.

Before downloading any database, make sure to read the terms of use and citation requirements, as some databases may have specific usage policies. Additionally, consider the compatibility of the database with your analysis pipeline and software tools.

NCBI 16s RNA database location ftp://ftp.ncbi.nih.gov/blast/db/16SMicrobial.tar.gz

Research Area:
pancreatic cancer; ovarian cancer; prostate cancer; bowel cancer; brain cancer; endometrial cancer; breast cancer; personalised medicine; high-throughput genomics

Link @ http://www.imb.uq.edu.au/sean-grimmond

Selected Topics:

Cluster Dynamics
Non-equilibrium Statistical Mechanics
Forced Systems
Hamiltonian Dynamics
Synchronization & Control
Genomics & Systems Biology
Computational Neuroscience
Econophysics

More @ http://www.jnu.ac.in/Conference/SCS2013/

Research Area

Developmental biology, Computational biology, Simulation modeling, Image data analysis

Link @ http://mysite.science.uottawa.ca/arolland/index.html

In comparative genome analysis work, we usually compare more than two genomes and looks for syntenic regions amongst them. In my research I used Evolution Highway (RH) http://eh-demo.ncsa.uiuc.edu/, which is a collaborative project designed to provide a visual means for simultaneously comparing genomes of multiple amniote species. The tool removes the burden of manually aligning these maps and allows cognitive skills to be used toward something more valuable than preparation and transformation of data. In addition to EH, attractive Circos (http://circos.ca/) is also very popular for this kind of analysis.

The EH is available online, and can be easily access and use, whereas Circos installation is not entirely straightforward. One of the most difficult parts of the installation involves installing the GD library. Since there weren't good instructions for installing this library on the internet I decided to post instructions here in case they are useful to anyone else.

Following are the steps to install GD modules in Mac OS

1. Setup

Create a folder for the files:

$ mkdir -p /SourceCache
$ cd /SourceCache

Get and unpack the required Jpeg-6b and GD libraries:
Download Jpeg-6b (http://code.google.com/p/google-desktop-for-linux-mirror/downloads/detail?name=jpeg-6b.tar.gz&can=2&q)
Download GD (http://search.cpan.org/~lds/GD-2.46/)

Place the "tar.gz" files in "/SourceCache" and double click to unpack.

2. Install libjpeg

Copy the "config.sub" and "config.guess" files to "/SourceCache". Note that your "config.sub" and ""config.guess" files may be in a slightly different location. The commands below show where they were on my machine:

$ cd /SourceCache/jpeg-6b/src
$ cp /usr/share/libtool/config/config.sub .
$ cp /usr/share/libtool/config/config.guess .

Configure libjpeg as follows. Note that this was installed on a 64 bit machine. However, this method may configure it in a 32 bit format. This may not be the best way to configure the installation but it works.

$ .configure --enable-shared
$ make

Check to see if the following directories exist on your machine. Create the missing directories in the following manner:

$ mkdir -p /usr/local/include
$ mkdir -p /usr/local/bin
$ mkdir -p /usr/local/lib
$ mkdir -p /usr/local/man/man1

Finish making and installing libjpeg:

$ make install

3. Install GD

$ cd /SourceCache/GD-2.46/GD/
$ perl Makefile.PL
$ make
$ make test (optional)
$ make html (optional)
$ make install

Other way for Mac OS
The easiest way to get a lot of these is with a program called Fink, which is similar in nature to the CPAN installer, but installs common GNU utilities. Fink is available from <http://sourceforge.net/projects/fink/>.

Follow the instructions for setting up Fink. Once it's installed, you'll want to run the following as root: fink install gd

It will prompt you for a number of dependencies, type 'y' and hit enter to install all of the dependencies. Then watch it work.

To prevent creating conflicts with the software that Apple installs by default, Fink creates its own directory tree at /sw where it installs most of the software that it installs. This means your libraries and headers for libgd will be at /sw/lib and /sw/include instead of /usr/lib and /usr/local/include. Because of these changed locations for the libraries, the Perl GD module will not install directly via CPAN, because it looks for the specific paths instead of getting them from your environment. But there's a way around that :-)

Instead of typing "install GD" at the cpan> prompt, type look GD. This should go through the motions of downloading the latest version of the GD module, then it will open a shell and drop you into the build directory. Apply below patch to the Makefile.PL file (save the patch into a file and use the command patch < patchfile.)

Then, run these commands to finish the installation of the GD module:

perl Makefile.PL
make
make test
make install
And don't forget to run exit to get back to CPAN.

Install on MS Window, using PPM

C:\Documents and Settings\Owner>ppm
PPM interactive shell (2.2.0) - type 'help' for available commands.
PPM> install GD
Install package 'GD?' (y/N): y
Installing package 'GD'...
Downloading http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW. ...
Installing C:\Perl\site\lib\auto\GD\GD.bs
Installing C:\Perl\site\lib\auto\GD\GD.dll
Installing C:\Perl\site\lib\auto\GD\GD.exp
Installing C:\Perl\site\lib\auto\GD\GD.lib
Installing C:\Perl\html\site\lib\GD.html
Installing C:\Perl\site\lib\GD.pm
Installing C:\Perl\site\lib\qd.pl
Installing C:\Perl\site\lib\auto\GD\autosplit.ix
PPM>


If you can't install it from ppm. You can download it:
http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW.


BTW,All Perl 5.6.1 Modules are located at:

http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW.

Install the Perl GD Module on Linux

$ sudo perl -MCPAN -e shell

Since it was the first time I had run this command on this particular machine I had to answer a lot of questions but simply selected the defaults for everything as this usually works for me. Once in the CPAN shell I entered

$ install Bundle::CPAN

and selected all of the defaults again. Once the CPAN bundle had finished installing I tried to install GD::Graph by typing

$ install GD::Graph

but it failed with hundreds of errors – the first of which was

GD.xs:7:16: error: gd.h: No such file or directory

This was fixed with the following apt-get command (in the bash shell)

$ sudo apt-get install libgd2-xpm-dev

back in the CPAN shell I still couldn’t get GD::Graph to build and I guessed this was because of some left over files from the failed build. I don’t know the command to clean things up inside the CPAN shell and am too lazy to read the docs so I simply went into the .cpan/build directory in my home directory and deleted anything that started with GD – eg

$ rm -rf GD-2.35-HC_vkB

$ rm -rf GDGraph-1.44-Evfibe

and so on. Those strings at the end (VkB and so on) look random so they might be different on your machine. Then I went back into the CPAN shell and ran

$ install GD::Graph

There were a few dependencies which the script fetched and installed for me but everything worked smoothly.

Manual and other Perl Module instalation are mentioned in my previous blog @ http://bioinformaticsonline.com/blog/view/710/how-to-install-perl-modules-manually-using-cpan-command-and-other-quick-ways

Use the Terminal or an Anaconda Prompt for the following steps.

1. To create an environment:

   conda create --name myenv
   

   NOTE: Replace myenv with the environment name.

2. When conda asks you to proceed, type y:

   proceed ([y]/n)?
   

This creates the myenv environment in /envs/. This environment uses the same version of Python that you are currently using, because you did not specify a version.

To create an environment with a specific version of Python:

conda create -n myenv python=3.4

To create an environment with a specific package:

conda create -n myenv scipy

OR:

conda create -n myenv python
conda install -n myenv scipy

To create an environment with a specific version of a package:

conda create -n myenv scipy=0.15.0

OR:

conda create -n myenv python
conda install -n myenv scipy=0.15.0

To create an environment with a specific version of Python and multiple packages:

conda create -n myenv python=3.4 scipy=0.15.0 astroid babel

TIP: Install all the programs that you want in this environment at the same time. Installing 1 program at a time can lead to dependency conflicts.

To automatically install pip or another program every time a new environment is created, add the default programs to the create_default_packages section of your .condarc configuration file. The default packages are installed every time you create a new environment. If you do not want the default packages installed in a particular environment, use the --no-default-packages flag:

conda create --no-default-packages -n myenv python

TIP: You can add much more to the conda create command. For details, run conda create --help.

➜ redundans git:(master) ✗ conda create --name py27 python=2.7
Solving environment: done

==> WARNING: A newer version of conda exists. <==
current version: 4.5.0
latest version: 4.5.2

Please update conda by running

$ conda update -n base conda

## Package Plan ##

environment location: /home/urbe/anaconda3/envs/py27

added / updated specs:
- python=2.7

The following packages will be downloaded:

package | build
---------------------------|-----------------
wheel-0.31.0 | py27_0 61 KB
python-2.7.15 | h1571d57_0 12.1 MB
certifi-2018.4.16 | py27_0 142 KB
sqlite-3.23.1 | he433501_0 1.5 MB
setuptools-39.1.0 | py27_0 582 KB
openssl-1.0.2o | h20670df_0 3.4 MB
pip-10.0.1 | py27_0 1.7 MB
ca-certificates-2018.03.07 | 0 124 KB
------------------------------------------------------------
Total: 19.6 MB

The following NEW packages will be INSTALLED:

ca-certificates: 2018.03.07-0
certifi: 2018.4.16-py27_0
libedit: 3.1-heed3624_0
libffi: 3.2.1-hd88cf55_4
libgcc-ng: 7.2.0-hdf63c60_3
libstdcxx-ng: 7.2.0-hdf63c60_3
ncurses: 6.0-h9df7e31_2
openssl: 1.0.2o-h20670df_0
pip: 10.0.1-py27_0
python: 2.7.15-h1571d57_0
readline: 7.0-ha6073c6_4
setuptools: 39.1.0-py27_0
sqlite: 3.23.1-he433501_0
tk: 8.6.7-hc745277_3
wheel: 0.31.0-py27_0
zlib: 1.2.11-ha838bed_2

Proceed ([y]/n)? y

Downloading and Extracting Packages
wheel 0.31.0: #################################################################################################################################################################################################### | 100%
python 2.7.15: ################################################################################################################################################################################################### | 100%
certifi 2018.4.16: ############################################################################################################################################################################################### | 100%
sqlite 3.23.1: ################################################################################################################################################################################################### | 100%
setuptools 39.1.0: ############################################################################################################################################################################################### | 100%
openssl 1.0.2o: ################################################################################################################################################################################################## | 100%
pip 10.0.1: ###################################################################################################################################################################################################### | 100%
ca-certificates 2018.03.07: ###################################################################################################################################################################################### | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
#
# To activate this environment, use:
# > source activate py27
#
# To deactivate an active environment, use:
# > source deactivate
#

➜ redundans git:(master) ✗ source activate py27