With advances in Cancer Genomics, Mutation Annotation Format (MAF) is being widley accepted and used to store variants detected. The Cancer Genome Atlas Project has seqenced over 30 different cancers with sample size of each cancer type being over 200. The resulting data consisting of genetic variants is stored in the form of Mutation Annotation Format. This package attempts to summarize, analyze, annotate and visualize MAF files in an efficient manner either from TCGA sources or any in-house studies as long as the data is in MAF format. Maftools can also handle ICGC Simple Somatic Mutation format.

maftools is on bioRxiv

Please cite the below if you find this tool useful for you.

Mayakonda, A. and H.P. Koeffler, Maftools: Efficient analysis, visualization and summarization of MAF files from large-scale cohort based cancer studies. bioRxiv, 2016. doi: http://dx.doi.org/10.1101/052662

Address of the bookmark: https://github.com/PoisonAlien/maftools

http://www.bx.psu.edu/~ratan/

Address of the bookmark: http://www.bx.psu.edu/miller_lab/

Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent or Master’s in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent with 4 years or 5 years of Bachelor’s degree having 1st Division or 60% marks or equivalent overall grade point average, with at least two years of research experience as evidenced from fellowship/ associateship/ training/ other engagements.

Knowledge in System Biology/ Statistical and computational Genomics/ Bioinformatics
Knowledge in computer programming, LINUX OS.
Expertise in use of R/other Bioinformatics software

More at http://iasri.res.in/employment/2017/cabin_advertisement_RA_SRF_YP_Mar2017.pdf

Phenomics of Moisture Deficit Stress Tolerance and Nitrogen Use December 31, 2019

Research Associate (RA) Two (2)

Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent or System Administrator/ Computer expert for database development, development of phenome data bank and virtual phenomics facility, data archiving and Efficiency in Rice and Wheat-Phase II (Funded by National Agricultural Science Fund, ICAR) Master’s in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent with 4 years or 5 years of Bachelor’s degree having 1st Division or 60% marks or equivalent overall grade point average, with at least two years of research experience as evidenced from fellowship/ associateship/ training/ other engagements. maintenance; Development of image analysis algorithms, APIs and IAPs.

Knowledge in System Biology/ Statistical and computational Genomics/ Bioinformatics
Knowledge of programming in LINUX/R/Perl/JAVA/PHP/JSP and use of various software & tools.
December 31, 2019

Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science / Computer Application or equivalent or Master’s in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent with 4 years or 5 years of Bachelor’s degree having 1st Division or 60% marks or equivalent overall grade point average, with at least two years of research experience as evidenced from fellowship/ associateship/ training/ other engagements.

Knowledge of Statistical and Computational Genomics/ Bioinformatics.
Knowledge of programming in LINUX/R/Perl/JAVA/PHP/JSP and use of various software & tools.
March 31, 2020

TMAP is a fast and accurate alignment software for short and long nucleotide sequences produced by next-generation sequencing technologies.

• The latest TMAP is unsupported. To use a supported version, please see the TMAP version associated with a Torrent Suite release below.

• Get the latest source code:

  git clone git://github.com/iontorrent/TMAP.git
   cd TMAP
   git submodule init
   git submodule update

https://github.com/iontorrent/TS/tree/master/Analysis/TMAP

Address of the bookmark: https://github.com/iontorrent/TS/tree/master/Analysis/TMAP

 All the nodes in the tree are clickable. This displays various information and options:

• The species name (and the associated common name if there is one)
• The rank (kingdom, family, class, species...)
• Ability to go to the corresponding node/species on NCBI web site (displayed in a new window)
• Possibility to download the corresponding subtree in newick extended format
• Possibilty to get the whole lineage from the current node/tip to the root of the tree.

Address of the bookmark: http://lifemap-ncbi.univ-lyon1.fr/

Date: April 24th. 2017 Last Date: May 6th 2017
PROJECT ID: 632

The following posts are urgently required to be filled for the Department of Biotechnology, Government of India funded project jointly running with IIIT-Hyderabad & JNU, entitled "Computational Core for Plant Metabolomics" administrated by Prof Indira Ghosh, School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi-110 067.
NB: For all the posts, preference will be given to candidates with a good knowledge of Python and/or R in UNIX platform , knowledge of JAVA will also get a special consideration.

1. RA / Research Associate (Metabolic engineering/Computational Biologist)

Salary: Rs. 36000/- + HRA

Vacancy: 1

Essential Qualifications: PhD in Bioinformatics /Mathematics/Computer Science with experience in analyzing high throughput omics-based data/Analysis of Network Biology/Chemoinformatics/Computational Biology related Software development. Published paper in the field is a must to prove the experience. Special consideration will be given if have experience in Industry, teaching & product development.

Desired Skills: Prior experience in handling and guiding bioinformatics, metabolomics data, planning of new research area in metabolic driven network , collaborating with industry , preparing and filing reports etc. Will be expected to communicate with user groups and coordinate with LIMS group in Hyderabad and the Cheminformatics group in Delhi.

2. Project SRF (Network model building/Systems biology integration)

Salary*: Rs.18000/- + HRA

Vacancy: 1

Essential Qualifications: M.Tech in Computational Biology with project experience or Masters / B.Tech in Basic Sciences with at least 2yrs of research experience in Bioinformatics/Mathematical Model building using Computational Biology tools & related Database / Network analysis etc. For M.Sc/B.Tech, Published paper in peer-reviewed Journal whereas for M.Tech, the degree obtained in computational biology is a must.

Desired Skills: Will be expected to manage ongoing research activities in LIMS, interact with LIMS group, build network model using data compiled by experimentalist, prepare and file reports and associated project work etc. Familiarity with plant systems biology and genomics /metabolite resources related to plant metabolomics is desirable.

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

https://bienkocrosettolabs.org/

We describe a new method for predicting the ancestral order and orientation of those intervals from their observed adjacencies in modern species. We combine the results from this method with data from chromosome painting experiments to produce a map of an early mammalian genome that accounts for 96.8% of the available human genome sequence data. The precision is further increased by mapping inversions as small as 31 bp. Analysis of the predicted evolutionary breakpoints in the human lineage confirms certain published observations but disagrees with others. Although only a few mammalian genomes are currently sequenced to high precision, our theoretical analyses and computer simulations indicate that our results are reasonably accurate and that they will become highly accurate in the foreseeable future. Our methods were developed as part of a project to reconstruct the genome sequence of the last ancestor of human, dogs, and most other placental mammals;

Address of the bookmark: http://www.bx.psu.edu/miller_lab/car/

Dr Altan Kara is a Bioinformatics specialist at the faculty of Gene Engineering and Biotechnology Institute at TUBITAK MAM Research Center. His research interest revolves around the cancer informatics and computational aided-drug design. I applaud Dr Altan for clearly setting out both his expectations of people that join his lab/university in addition to listing his responsibilities to his research members at TUBITAK MAM Research Institüte. Hopefully, this interview will prove useful to others in the field, especially to those who are just starting their bioinformatics careers.

You can find out more about Dr Altan by visiting his (well documented) lab page (http://gmbe.mam.tubitak.gov.tr/en) and BOL page http://bioinformaticsonline.com/profile/altan . And now, on to the BOL:“Tryst with a Bioinformatician” interview series ...

• What push you to join Computational Biology/Bioinformatics?

According to me, bioinformatics is the center of modern biological research and if a researcher wants to discover new biological insights by evaluating the globally produced biological data to derivate unified solutions for specific biological problems, learning bioinformatics is the only way to achieve this goal.

• What fascinates you about Computational Biology/Bioinformatics?

It's flexibility. As well known, there are highly diverse and complex biological questions are waiting to be enlightened and it's impossible to bring solutions to this diversity by using similar approaches. Thus, the employed method has to be unique for the targeted biological problem and by using bioinformatics tools this can be easily achieved. 

• What is the one word you would use to describe yourself?

Bioinformatician. :)

• Can you please describe your research work in a nutshell for BOL users.

At my current Institute, I am working in the field of cancer bioinformatics. Briefly, the overall aim of the project which I am working for (AKMARK (Project CODE:5153403)) is, applying a bioinformatics-supported genome, transcriptome, proteome, and metabolome analysis to reveal the molecular profile of the disease through an integrated approach, and to develop an early diagnosis and scanning kit based on this profile. Alterations in the gene, transcript, protein, and metabolite profiles between normal tissue, normal tissue adjoined to the tumor (reactive stroma), tumor tissue, lymph node metastasis, and blood samples taken from the same patient and the reflection of these changes in some other selected body fluids will be revealed within the scope of the project. The molecular structures involved in the development and progression of NSCLC will be determined and relations with the clinical, tumor-node-metastasis (TNM) staging and histology will be made. The development of a diagnostic kit for immediate clinical purposes and an electrochemical biosensor for quick on-site applications are targeted through the development of a number of antibody and aptamer formed against the most specific biomarker selected from the panel.

• Is there anything else we should know about you and your research?

Besides AKMARK, I am also in preparation of having a side project that aims for the development of a computational method to design inhibitors for prokaryotic two-component systems. In this project, I will be in collaboration with Prof. Maria Kontoyianni, SIUE: Southern Illinois University Edwardsville, School of Pharmacy.

• What was your greatest scientific disappointment in life till now?

So far I do not experience any memorable scientific disappointment in my life. :)

• What major research challenges and problems did you face yet? How did you handle them?

The major challenge which I faced so far in my scientific career was predicting the interaction between the prokaryotic two-component proteins. To be able to accurately predict the interactions between these proteins, I create a meta-predictor by using a support vector machine. By using this technique I integrated six different protein-protein interaction methods in a way to cover disadvantage of one method with the advantage of another one. The meta-predictor which I developed during this work is accessible via http://metapred2cs.ibers.aber.ac.uk/ and for more detailed information about the system the articles with the PMID IDs; PMID: 27378293 and PMID: 26384938 can be read.

• What's your all-time favourite bioinformatics package, and why?

For me, the best bioinformatics package is R/Bioconductor. The reason why I like this package is, it provides lots of useful tools for comprehensive analysis and comparison of high-throughput experimental data in an integrated manner and besides lots of the packages it provides, it is open source and also open for development. As a result, it provides strong and flexible ways to do science.

• In bioinformatics, do you see yourself in which of the following roles-scientist, analyst, developer, engineer or pure academician?

Scientist / Developer.

• What will you like to accomplish in next five years / ten years?

For my current research, I would like to design a pipeline to automatically integrate and analyse omics data for cancer research which will be specifically aiming for biomarker and novel drug target discovery. In addition to this, I also like to develop another pipeline for prokaryotic TCS protein structure prediction and inhibitor design.

• When you will be retired, what would you tell next generation bioinformaticians?

Bioinformatics is not all about scripting and researchers who study in this field should never expect a tool to do their analyses for them. Besides computational skills, a bioinformatician must have a strong biological background in his/her research area which will allow them to understand if anything went wrong during their run by only looking at the results instead of just blindly trusting the output of the bioinformatics tools.

• What you always miss in bioinformatics when you will no longer working in this field?

Bioinformatics is open to doing multi-discipliner research with scientists all around the world. As a result, while I studying in this field I can interactively learn a lot from wide range research community. I think this is the one thing which I will miss the most.

• If there will be bioinformatics company owned by you in future, What are your company focus and aim?

With the increasing amount of data in databases, there is already a massive need for effective methods to eliminate the manipulated data and reach to clean/useful information. As days pass, the requirement of data mining will be the first step of any research project. For this reason, the major goal of my bioinformatics company will be developing effective tools to eliminate manipulated datasets and information that exist in the literature and provide trustworthy clean information/datasets for researchers.

• How much bioinformatics change in 2050, according to your wild imagination?

Bioinformatics is a field that constantly and dynamically changes. As the bioinformatics progress, new tools and methods become available and they provide a better application of existing methods or totally new methods that offer an alternative solution to various biological problems. A long with these updates, developers also provide easy to use GUIs for most of the tools. Considering this, if the field carries on developing like this, every single researcher with a strong biological background can be able to perform bioinformatics analyses by him/herself without needing a professional help. As a result, almost all of the bioinformaticians will be responsible just for development of new methods/tools.

• What would one piece of advice you give someone who's trying to reinvent themselves and enter into bioinformatics sector?

Bioinformatics is a wide field with a lot of career options. Thus, if a researcher likes to step into this field first he/she should be clear about the branch of the bioinformatics they like to study in. Following to this decision they should first learn at least one programing language and investigate the ways of how other researcher employed that language in their researches and WHY? A researcher, in this field, should never create and use copy paste scripts but always must understand WHY the other researcher worked in that way. Knowing the answer of this question is the only way to learn bioinformatics. Besides, a researcher in the field of bioinformatics (from any branch) must always be good about the environmental control. In other words, one should always easily control input output directories, modify files or directories, annotate and modify employed scripts during the research and should not allow any confusion during the different stages of the research. Finally, they should not blindly trust the output of a tool/software but do a benchmarking test for each of the tools which they decided to utilise in their research. In addition to this, even if the tools pass the benchmarking, researchers should have a good biological background in their field to tell if anything when wrong during the process by only looking the output(s) of the employed pipelines/packages/tools.  

We are now seeking a postdoc scholarship holder with strong background in transcriptomics to use this large collection of data for integrative studies. Focus will be on advanced bioinformatics and statistical analysis of data from high-throughput sequencing including integration with the other platforms.

The scholarship holder must have a PhD with an outstanding research and publication record and will be selected based on her/his excellence and her/his skills. A PhD should have been awarded less than five years before the deadline of the application. The scholarship holder must have a strong background in bioinformatics, computer science, computational biology or equivalent with a profound knowledge about biology and biostatistics.

Your complete application must be received at KTH no later than 2018-01-15.

https://www.kth.se/en/om/work-at-kth/stipendier/postdoctoral-scholarship-in-bioinformatics-with-focus-on-transcriptomics-and-data-integration-1.779571