BOL: Related items

Illumina Smartphone Chip !!!

Robert M Willioms — Tue, 30 Dec 2014 23:19:54 -0600

Illumina, the company that claims it brought human genome sequencing down to $1000 prices, has now turned its attention to a consumer product - a chip that you can plug into your smartphone and have it read your genetic information.

The biggest challenge ahead of Illumina is simplifying the process of genetic sequencing. Currently, Illumina’s DNA sequencers are gigantic machines that use techinques like colorimetry to work, but while the core technology is computational, it takes some 30 steps to extract genetic data and run it through. This process will likely have to be hugely simplified on mobile devices, given the fact that some studies require extracting 10 mililiters of blood. Illumina researchers are also working on finding the optimal technology for this on-chip DNA sequencing - be it electrical, optical, or other.

Illumina is one of the most prominent names in genetics, often said to be the Intel of genetic sequencing, as just like Intel it provides the algorithms, the processing brain that runs a DNA reading task.

In other recent smartphone-related biotech news, drug company Pfizer launched its REMOTE project, a new type of clinical trial that does not require going to a hospital for checks - targeted at patients with overactive bladder problems, the FDA-approved REMOTE project allowed to gather data from patients from over 10 states remotely, via mobile devices.

This is indeed the Illumina answer to Apple's Health app, HealthBook, Google HealthFit.

Understanding kmer !

BioStar — Wed, 18 Aug 2021 04:27:51 -0500

What is a k-mer anyway? A k-mer is just a sequence of k characters in a string (or nucleotides in a DNA sequence). Now, it is important to remember that to get all k-mers from a sequence you need to get the first k characters, then move just a single character for the start of the next k-mer and so on. Effectively, this will create sequences that overlap in k-1 positions.

Address of the bookmark: https://bioinfologics.github.io/post/2018/09/17/k-mer-counting-part-i-introduction/

WALK-IN-INTERVIEW for the post of JRF and Project Assistant @ CIFT

Tue, 20 Jan 2015 23:03:20 -0600

Eligible candidates are invited to attend a walk-in-Interview with all relevant documents for the following positions of Project Fellows (on contractual basis) to work in the Project “ Genetic Diversity of Clostridium botulinum in seafood and Development of Lateral Flow Immuno Assay (LFIA) for toxinotyping funded by Department of Biotechnology. The duration of the project is 3 years / co-terminus with the scheme.

Jr. Research Fellow – 2 posts

Fellowship : Rs. 25000/- + 20% HRA pm for Ist & 2nd year and Rs.28000/- + HRA on 3rd year

Qualification : Ist class Masters Degree in Microbiology/Fishery Microbiology/Bio-technology.

Desirable :

1. CSIR/UGC NET/JRF qualified

2. Excellent analytical skills and computer documentation

3. Prior experience in handling microbial cultures and molecular techniques

Project Assistant – 1 post

Fellowship : Rs.8000/- p.m (consolidated)

Qualification: Masters degree in Microbiology/Biotechnology with skill in Bioinformatics

Desirable: Excellent analytical skills in Bioinformatics and computer documentation

Terms & Conditions:

Registration will begin at 8.30 a.m and will close at 11.00 am
Age limit (as on 29.1.2015): Below 35 years for men and 40 years for women.
Age relaxation of 3 year for OBC candidates and 5 years for SC/ST candidates is permissible.
Candidates are required to submit self-attested copies of all the Certificates in support of their claims regarding age, educational qualifications, scheduled caste/scheduled tribe/OBC etc. The original certificates shall be produced for verification before the interview.
Candidates should bring detailed bio-data (in the enclosed format) affixing a recent passport size photograph.
The selected candidate will be recruited on contract basis under ICAR norms. The post is purely temporary and is co-terminus with the project.
The candidates attending the interview should ensure that they fulfil all the eligibility conditions. No correspondence will be entertained from the candidates for selection/test/appointment.
No TA/DA will be paid to attend the interview.
Canvassing in any form will render the candidate disqualified for the post.
The Director’s decision will be final and binding in all aspects regarding the selection to the post.

Venue: CIFT, Matsyapuri.P.O, Cochin Date of interview: 29.01.2015 Time: 10.00 am

http://www.cift.res.in/uploads/userfiles/file/file/srf%20appn.doc

MitoZ: a toolkit for animal mitochondrial genome assembly, annotation and visualization

Neel — Tue, 30 Nov 2021 23:23:57 -0600

MitoZ, consisting of independent modules of de novo assembly, findMitoScaf (find Mitochondrial Scaffolds), annotation and visualization, that can generate mitogenome assembly together with annotation and visualization results from HTS raw reads.

https://academic.oup.com/nar/article/47/11/e63/5377471

Address of the bookmark: https://github.com/linzhi2013/MitoZ

WALK-IN-INTERVIEW FOR PROJECT ASSISTANT @ BHARATHIDASAN UNIVERSITY

Mon, 12 Jan 2015 21:54:10 -0600

BHARATHIDASAN UNIVERSITY
DEPARTMENT OF BIOINFORMATICS, SCHOOL OF LIFE SCIENCES, TIRUCHIRAPPALLI – 620024

Project title: “Genome-scale metabolic modeling and simulation of rumen methanogens An in silico attempt to methane attenuation”

Funding Agency: University Grants Commission, New Delhi

Tenure of the project: Two years or till the end of the project period.

Position: Project Assistant (1 no.)

Essential qualification: First class M.Sc. in Bioinformatics/Microbiology/ Biotechnology and other related discipline.

Desirable qualification: Experience in an area relevant (Molecular Systems Engineering) to the project.

Fellowship: Rs. 5000 per month as per the UGC norms.

Upper age limit: 28 years

Date of Venue of interview: 22.01.2015, Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tiruchirappalli -620 024, Tamil Nadu

The above post is purely temporary and will be terminated with three month notice.

The Terms and the condition of the appointment shall be governed according to UGC, Govt. of India. The eligible candidates will bring their original certificates and documents at the time of interview. No TA/DA will be paid for attending the interview.

Dr. P. CHELLAPANDI
UGC-Research Awardee,
Department of Bioinformatics,
School of Life Sciences,
Bharathidasan University,
Tiruchirappalli -620 024, Tamil Nadu

Advertisement: www.bdu.ac.in/adv/PA_UGC_Bioinformatics.pdf

maftools

Surabhi Chaudhary — Fri, 17 Dec 2021 03:18:28 -0600

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

https://www.bioconductor.org/packages/devel/bioc/vignettes/maftools/inst/doc/maftools.html

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

Linux operating system aimed at scientists

Pranjali Yadav — Mon, 19 Jan 2015 08:30:49 -0600

The Bio-Linux operating system is based on Ubuntu 14.04 LTS (Trusty Tahr), and the previous version was using Ubuntu 12.04 LTS. The developers only use LTS releases and that means that upgrades for this distro don't come along all that often.

This Linux distribution is aimed at scientists and it comes with more than 250 bioinformatics packages, 50 graphical applications and several hundred command line tools. And this is just skimming the surface of what the OS can do. Users have access to even more apps from the official repositories.

Bio-Linux is using an Ubuntu LTS version as its base

The fact that it uses Ubuntu LTS versions for the base is a good thing because it means its users won't have to worry about the support. Ubuntu 14.04 LTS is supported until 2019, so people who are using Bio-Linux shouldn't have a problem.

"An updated Bio-Linux 8 version is now on the website in ISO and OVA versions. As usual, there is no need to download this version if you are an existing user. All updates to existing packages will be applied to your system through the update manager and new packages are all available via apt-get or Synaptic," reads the announcement.

The changelog also states that a problem that was preventing the desktop to not start on VirtualBox has been fixed, the QIIME and Bowtie-Bio tools have been upgraded, the pandaseq paired end assembler has been added, and the beginners tutorial specific to Bio-Linux 8 has been improved.

Check out the official announcement for a complete list of changes and updates. You can download Bio-Linux 8.0.5 right now from Softpedia and give it a spin. It has the Unity desktop and now it runs very well in virtual environments.

Reference @ http://news.softpedia.com/news/Bioinformatics-Distro-Bio-Linux-8-0-5-Now-Available-for-Download-469867.shtml

Short-read assembly using Spades !

Abhimanyu Singh — Mon, 31 Jan 2022 07:18:16 -0600

If we only had Illumina reads, we could also assemble these using the tool Spades.

You can try this here, or try it later on your own data.

Get data

We will use the same Illumina data as we used above:

illumina_R1.fastq.gz: the Illumina forward reads
illumina_R2.fastq.gz: the Illumina reverse reads

Assemble

Run Spades:

spades.py -1 illumina_R1.fastq.gz -2 illumina_R2.fastq.gz --careful --cov-cutoff auto -o spades_assembly_all_illumina

-1 is input file of forward reads
-2 is input file of reverse reads
--careful minimizes mismatches and short indels
--cov-cutoff auto computes the coverage threshold (rather than the default setting, “off”)
-o is the output directory

Results

Move into the output directory and look at the contigs:

infoseq contigs.fasta

DNA Transcription (Advanced)

Thu, 29 Jan 2015 05:31:42 -0600

Transcription is the process by which the information in DNA is copied into messenger RNA (mRNA) for protein production. Originally created for DNA Interactive ( http://www.dnai.org ). TRANSCRIPT: The Central Dogma of Molecular Biology: "DNA makes RNA makes protein" Here the process begins. Transcription factors assemble at a specific promoter region along the DNA. The length of DNA following the promoter is a gene and it contains the recipe for a protein. A mediator protein complex arrives carrying the enzyme RNA polymerase. It manoeuvres the RNA polymerase into place... inserting it with the help of other factors between the strands of the DNA double helix. The assembled collection of all these factors is referred to as the transcription initiation complex... and now it is ready to be activated. The initiation complex requires contact with activator proteins, which bind to specific sequences of DNA known as enhancer regions. These regions may be thousands of base pairs distant from the start of the gene. Contact between the activator proteins and the initiation-complex releases the copying mechanism. The RNA polymerase unzips a small portion of the DNA helix exposing the bases on each strand. Only one of the strands is copied. It acts as a template for the synthesis of an RNA molecule which is assembled one sub-unit at a time by matching the DNA letter code on the template strand. The sub-units can be seen here entering the enzyme through its intake hole and they are joined together to form the long messenger RNA chain snaking out of the top.

Smudgeplot: Inference of ploidy and heterozygosity structure using whole genome sequencing data

Neel — Fri, 25 Feb 2022 04:42:09 -0600

This tool extracts heterozygous kmer pairs from kmer count databases and performs gymnastics with them. We are able to disentangle genome structure by comparing the sum of kmer pair coverages (CovA + CovB) to their relative coverage (CovB / (CovA + CovB)). Such an approach also allows us to analyze obscure genomes with duplications, various ploidy levels, etc.

Smudgeplots are computed from raw or even better from trimmed reads and show the haplotype structure using heterozygous kmer pairs. For example:

Address of the bookmark: https://github.com/KamilSJaron/smudgeplot