https://gist.github.com/santhilalsubhash/367befcf5216be4b1fd9

Information:

This script converts EnsEMBL GTF (Ex: https://gist.githubusercontent.com/santhilalsubhash/1e7cca357e52a181dc25/raw/cfb803e07900a2baefbb6534f1299fd30cb57a29/sample.GTF) file to annotation table format. It generated two files
1) Transcript wise chromosome location with information about transcripts (Ex: https://gist.githubusercontent.com/santhilalsubhash/c7dec516e0338503a4b6/raw/de0af1a39f0005c4ce7321c5ae57fc8b4a14c7f4/sample.GTF_enst_annotation.txt)
2) Gene wise chromosome location with information about genes (Ex: https://gist.githubusercontent.com/santhilalsubhash/c92006c5080f0333bec2/raw/d16e0b2440d73b09b486d3c9751cdb248a73fa0b/sample.GTF_ensg_annotation.txt)

Note: You can download GTF files from http://www.ensembl.org/info/data/ftp/index.html

Address of the bookmark: https://github.com/dhlbh/BASE

For more background see also the publication at BMC Bioinformatics.

https://github.com/clwgg/nQuire

Address of the bookmark: https://github.com/clwgg/nQuire

The symposium will focus on topics in the below mentioned areas.

Topics: Algorithms for biomolecular sequences / structures Bioinformatics databases and tools Protein function Structure based drug design Machine learning Deep learning Large scale data analysis Big Data NGS Analysis Protein interactions/network Molecular modelling/docking/screening Biomolecular structure and function More

Info: https://web.iitm.ac.in/bioinfo2/symposium2020/home

Age Limit: 35

How to Apply for the AIIMS Life Science Job:

Interested applicants are asked to send out a detailed CV to Dr Ashok Sharma (aioncoaiims@gmail.com). Laboratory of Chromatin and also Cancer Epigenetics, Department of Biochemistry with the subject line “Application for Scientist-B position for MeitY project” latest by January 01st, 2021.
Complete Information of the year of passing, experience, marks, etc. ought to be mentioned in the CV Incomplete. applications will certainly be rejected Just shortlisted applicants will be called for interview. Chosen candidates will certainly be intimated by email/phone.
No TA/DA will certainly be paid for appearing in the interview.
Note, The institute reserved the right to fill up or not to fill up the post advertised.

Emoluments: Rs. 56,000/- plus 24 percent HRA

Eligibility:
2nd class Master’s Degree with a PhD in a pertinent subject (Bioinformatics) from.a recognized University
1st class Master’s degree in Life Sciences (Bioinformatics) from a recognized university OR.
Bachelor’s Degree in Engineering or-Technology with minimal 60% marks from a recognized University or equivalent.

Desirable Qualifications:
Experience in Bioinformatics/NGS data. Analysis/System Biology/Computer Science/ statistics with experience in Machine learning/Al project.
Experience of Deep learning applications in biological data ( image/text).
Proficient in Rf Python machine learning libraries.
Prior experience in the cancer-related project (ML-based) will be advantageous.
Experience with PyTorch/TensorFlow will certainly be very desirable.
Applicant should have strong scientific writing as well as. verbal abilities.
Papers in sci-indexed journals demonstrating ML skill sets.
Database handling will certainly be plus yet not required.

More detail at https://www.aiims.edu/images/pdf/recruitment/advertisement/biochem-16-12-20.pdf

Requirements
Doctoral degree in Bioinformatics, Computational Biology, (Bio)physics/-mathematics, Biochemistry/Biology or similar with strong quantitative and numeric focus
Ability to numerically process complex and large data sets
Good programming skills (R/Bioconductor and/or Python preferred, Linux is a plus)
Experience in analyzing next-generation sequencing data sets using network biology
Scientific publication record in applied bioinformatics
Familiarity with single cell NGS analyses and other –omics techniques is a plus, but not essential

1. Illumina, Inc. (U.S.)

Illumina, Inc. was founded in 1998 and is headquartered at San Diego, U.S. Illumina, Inc. is one of the leading players in DNA sequencing and array-based technologies, serving customers in the research, clinical, and applied markets. The company offers products for applications in the life sciences, oncology, reproductive health, agriculture, and other emerging segments. The company serves government laboratories, genomic research centers, academics institutions as well as pharmaceutical, biotechnology, agrigenomics, commercial molecular diagnostics laboratories and consumer genomics companies. Illumina, Inc. has its geographic presence in North America, Europe, Latin America, Asia-pacific, and others.

2. QIAGEN N.V. (Netherlands)

QIAGEN N.V. was incorporated in 1986 and is headquartered at Venlo, The Netherlands. The Company is engaged in providing Sample to Insight solutions that transform biological samples into molecular insights. QIAGEN provides its workflow to customers in molecular diagnostics, assay technologies, bioservices and automation systems.  The company’s genome services are suitable for custom/tailored projects that allow access to genomic sequence information.  The Company market its products in more than 100 countries across the Americas, Europe, Asia, Australia, and the Middle-East &Africa through its subsidiaries and channel partners.

3. PerkinElmer, Inc. (U.S.)

PerkinElmer, Inc. was founded in 1947 and is headquartered in Waltham, Massachusetts, the U.S. PerkinElmer, Inc. offers its products & services and solutions for the diagnostics, food, environmental, industrial, life sciences research and laboratory services markets. The company offer comprehensive genetic testing solutions that help to provide insight into the complex nature of rare and inherited diseases. Some of the subsidiaries of the company are Caliper Life Sciences, Improvision, Viacell Inc., ViaCord LLC, among many others. The company has its facilities located in Europe (France, Germany, and Belgium), U.S. and Asia (China, India, and Japan).

4. Eurofins Scientific SE (Luxembourg)

Eurofins Scientific SE was founded in 1987 and is headquartered in Luxembourg, Europe. The company offers a portfolio of over 130,000 analytical methods and more than 150 million assays performed each year to establish the safety, identity, composition, authenticity, origin, traceability, and purity of biological substances and products, as well as carry out human diagnostic services. The company has its geographic presence across 39 countries in Europe, North and South America, and Asia-Pacific.

5. GATC Biotech AG (Germany)

GATC Biotech AG was founded in 1990 and is headquartered in Constance, Germany. The company provides DNA and RNA sequencing and bioservices solutions to academics and industrial areas. It also provides next generation sequencing services including genomes, targeted (re)-sequencing, human sample sequencing, transcriptomes, metagenomes, regulomes, pre-sequencing, NGS barcode labels, and next generation sequencing technologies; and bioservices services, including bioservices tools, pipelines and workflows, compute resources, data analysis reports, and case studies. GATC Biotech AG operates as a subsidiary of Eurofins Scientific SE. It offers its products through distributors in Italy, Japan, Portugal, Spain, and the Czech Republic.

6. Macrogen, Inc. (South Korea)

Macrogen, Inc. was founded in 1997 and is headquartered in Seoul, South Korea. Macrogen, Inc. provides next generation sequencing services such as whole genome, de novo, exome, targeted, transcriptomics, metagenome, and epigenome sequencing.  The company also provides a variety of services such as oligo synthesis, database construction, genome research, and bioservices analysis system consulting services. Macrogen, Inc. provides genome research services in Korea and internationally.

7. Genotypic Technology Pvt. Ltd. (India)

Genotypic Technology Pvt. Ltd. was incorporated in 1998 and is headquartered in Bangalore, India. Genotypic Technology is the first Genomics service provider in India providing Microarray, Next Generation Sequencing (NGS), Bioservices and solutions to domestic/ international pharma, biotech companies and academia. The company provides its services for protocol optimization, probe designing, array layouts, project designing, and nucleic acid analysis to in-depth analysis. Genotypic Technology has its geographic presence in North America, Europe, Asia Pacific, Middle East & Africa, and Latin America.

8. GENEWIZ, Inc. (U.S.)

GENEWIZ, Inc. was founded in 1999 and is headquartered in South Plainfield, New Jersey, the U.S.; The company is a leading provider of research service in the field of Next Generation Sequencing, Sanger DNA sequencing, sequencing of bacteria and phage, gene synthesis, DNA cloning, genomics including mutation analysis, single nucleotide polymorphism, and bioservices. GENEWIZ, Inc. has its geographic presence in U.S., China, Germany, France, Japan, and the U.K.

9. Beijing Genomics Institute (China)

Beijing Genomics Institute (BGI) is the world’s largest genomics organization and non-profit research institution that was founded in 1999 and is headquartered in Shenzhen, China. The Company provides a wide range of commercial next generation sequencing services and genetic tests for medical institutions, agricultural and environmental applications. The Company operates all across the globe through its subsidiaries, namely, BGI China (Mainland), BGI Asia Pacific, BGI Americas (North and South America) and BGI Europe (Europe and Africa).

10. SciGenom Labs Pvt. Ltd (India)

SciGenom Labs Pvt. Ltd was founded in 2010 and is headquartered in Cochin, India with offices in Chennai & Hyderabad in India, and San Francisco in the U.S. It is a Genomics R&D services company that provides genomic sequencing and NGS services to life sciences and healthcare businesses globally as well as academic and government institutions in India.

Popular mentions – MedGenome (India), DNA Link, Inc. (South Korea), Otogenetics Corporation (U.S.), Novogene Corporation (China), LGC Limited (U.K.), CD Genomics (U.S.), SeqLL, LLC (U.S.)

Address of the bookmark: http://pacb.com/blog/the-hifi-difference-true-long-reads-vs-synthetic-long-reads/

The prepint version is found on http://www.biorxiv.org/content/early/2017/08/09/173872

It uses the pyPaSWAS framework for sequence alignment (https://github.com/swarris/pyPaSWAS)

Address of the bookmark: https://github.com/swarris/Pacasus

The most common newbie questions are:

Should I try to use these free open source programs?  Why are we not trying GUI software for computational analysis? Should I use commercial bioinformatics programs/software?”

1. Let’s be open

We generally think free and cheap are useless. But this concept is not applicable when we discuss open source software. Mostly, the bioinformatics software is developed by highly competitive biological programmers who believe in open sharing of knowledge. They come under Open Bioinformatics Foundation or O|B|F which is a non-profit, volunteer run organization focused on supporting open source programming in bioinformatics. The best part about open source tools/software is that they’re free to download the source code and read exactly what the program does. If you are so inclined, you can view all of the parts of the program and see the logical flow of the pipeline. In addition, open source makes an excellent learning tool for any beginning bioinformatician. Moreover, you can modify existing open source programs to deal with cutting-edge problems or to customize your pipeline. Apart from your computational and analysis work, most of the reviewer also prefers the open source based results so that they can validate the results if validation required.

2. Code headache

As a bioinformatician you are supposed to know the basics of programming languages, and if you are not good at it, then please learn it as soon as possible because you are not a bio-analyst but biological programmers. The open source programs usually lack dedicated service and support teams (often because they were the product of an overworked doc/postdoc!) so you are responsible for troubleshooting your own errors most of the time. We commonly receive the HELP email to support and assist to setup the pipeline; you can also find this kind of request on any QA forum. I personally believe this coding horror brings the biggest downside of open-source programs; where you need some programming skills in order to implement the program in your pipeline. But, if you are not able to fix the pipeline and modify the open source code according to your requirements them you should re-think on your bioinformatician name tag!!!

3. Dive into the codes

Some of the biologist turn bioinformatician says “if you can do the same thing with commercial software then why to get migraine with weird codes”, well this statement looks to me that guys are keen to learn swimming but still don’t like to get wet. If you are still using paid software and doing your work by customer support and clicking some of the well-designed GUI button then perhaps you are not interested in learning and trying new and challenging bioinformatics works. You are missing the basic flavour of bioinformatics. Let’s dive into the coding world, I am sure your will enjoy it. I recommend your to swim freely in code’s sea, and enjoy the journey; do not merely watch it from the outside.  

4. Paid does not mean better

The bioinformatics company which are specializes in bioinformatics solutions develop well designed/packed, user friendly software by using a large number of specialised scientist, programmers and support staff. They also provide good services to accomplice your biological analysis work. This means that if you hit a ‘snag’ with your data, help is likely only a phone call away! These companies price their products competitively against the cost of a dedicated bioinformatician. You may be able to afford the program, but not the additional staff! Additionally, most of the functionality that you need in your analysis is already coded into the program. Need to plot a graph? Just click this button right here. It is that easy. But, as a bioinformatician this is not generally well encouraged approach in biological analysis work, because the software is not available to everyone and your data can’t be validated. Moreover, there is very less chances that anyone will repeat your work or love to do similar kind of research (because not all the labs in the world are rich like yours).

5. Take a caution

In biological analysis work, in which you deal GB/TB of data are having maximum chances of getting errors, so please be careful and always cross check your data before coming to any conclusion. Even an error in two line code can alter your entire analysis and display weird results. Some of the scientist blindly believes on commercial software, which is entirely wrong. Using proprietary tools does not absolve you of the need to actually read and research the type of analysis that you are doing. This is particularly true in the case of genome assembly and annotation.

At the end, I would like to tell only one think that open source solutions allows you to do more cutting edge analysis than the commercial tools. So let’s go for it.

Disclaimer:

This is my personal view. I have nothing to do with any company or open source community. The views expressed on these pages are mine alone and not those of my current/past employers. I do reserve the right to remove comments left by spammers or off-topic comments.