BOL: Related items

SvABA: Structural variation and indel detection by local assembly

Jit — Tue, 10 Mar 2020 07:52:15 -0500

SvABA is a method for detecting structural variants in sequencing data using genome-wide local assembly. Under the hood, SvABA uses a custom implementation of SGA (String Graph Assembler) by Jared Simpson, and BWA-MEM by Heng Li. Contigs are assembled for every 25kb window (with some small overlap) for every region in the genome. The default is to use only clipped, discordant, unmapped and indel reads, although this can be customized to any set of reads at the command line using VariantBam rules. These contigs are then immediately aligned to the reference with BWA-MEM and parsed to identify variants. Sequencing reads are then realigned to the contigs with BWA-MEM, and variants are scored by their read support.

Address of the bookmark: https://github.com/walaj/svaba

RA Bioinformatics at NATIONAL INSTITUTE OF BIOMEDICAL GENOMICS, INDIA

Wed, 26 Jul 2017 03:49:52 -0500

NATIONAL INSTITUTE OF BIOMEDICAL GENOMICS
(An Autonomous Institution of the Government of India)
P.O.: N.S.S., Kalyani 741251, West Bengal

Advertisement No. 137/ESTB/NIBMG/17-18

Position available Project Description: Several positions are available for the project titled: “A unified web-portal for analysis, integration and visualization of multi-omics data”. The goal of this project is to develop a user-accessible resource for integrated analysis and visualization of multi-OMICs data sets (including gene expression, genotype, methylation, microRNA, etc.). Data sets generated on various platforms shall be maintained in a stable database, accessed through standard querying mechanisms, and the results shall be displayed via user-friendly interface. The analysis engine shall run on open-source software (such as R/Bioconductor) developed in-house. All positions are contractual.

Appointment will be initially given for a period of one year which is extendable depending upon performance, availability of funds and requirements of the institute.

Project Code: 20275 Position: (No. of positions available)

Research Associate (3)

Position 1: Ph.D. or equivalent in statistics, computer science, mathematics, bioinformatics, or related subject.
Position 1: Those with experience in database management shall be preferred. Experience with UNIX or GNU/Linux operating system.
Position 1: Creation and maintenance of a database for population- and diseaseassociated variation resource. Development of programmatic interface for querying the database, filtering of the results and identification of genes of interest.

Rs. 36000/- + 10% HRA

Please apply online via web link http://apply.nibmg.ac.in/ (no other form of application will be accepted). The last date of application is 14-08-2017. All letters to attend screening test and /or interview will be sent only to the short-listed candidates by Email only. No correspondence will be made with applicants who are not shortlisted /not called for screening test and /or interview. No TA/DA will be paid for attending the screening test and /or interview.
Detail information at http://www.nibmg.ac.in/academic/Advt_20275.pdf

More Info: http://www.nibmg.ac.in/?q=Project%20Linked%20Personnel

RefKA: A fast and efficient long-read genome assembly approach for large and complex genomes

Rahul Nayak — Fri, 01 May 2020 03:00:40 -0500

RefKA, a reference-based approach for long read genome assembly. This approach relies on breaking up a closely related reference genome into bins, aligning k-mers unique to each bin with PacBio reads, and then assembling each bin in parallel followed by a final bin-stitching step.

Address of the bookmark: https://github.com/AppliedBioinformatics/RefKA

Bioinformatics lectures !

Jit — Wed, 29 Nov 2017 05:39:54 -0600

Computational Biology is a huge field of study, that touches upon many distinct algorithmic and biological areas of study. What we are able to cover in this course will depend, in part, on the pace at which we move, which I will attempt to adjust as appropriate. However, here is a tentative list of topics I hope to cover this semester (not necessarily in order).

Optimal sequence alignment (global, local, and glocal alignment &mdash with constant & affine gap penalties
Algorithms and data structures for efficient text indexing and exact search
Heuristics for read alignment and mapping &mdash mapping DNA-seq and RNA-seq reads
Genome assembly &mdash k-mers, De Brujin graph construction and representation, long-read technology and read-overlap graph assembly
Motif finding via Gibbs sampling
Gene finding &mdash statistical models for ab initio and evidence-guided prediction of genes
RNA-seq and transcriptomics &mdash transcript assembly, abundance estimation and differential expression testing
Phylogenetics &mdash The small and large phylogeny problem; parsimony, maximum likelihood and Bayesian methods

Address of the bookmark: https://rob-p.github.io/CSE549F16/lectures/

India and Germany to begin joint research in the area of 'Bioinformatics in Health Research'

Rahul Nayak — Wed, 17 Jan 2018 14:10:36 -0600

To facilitate bilateral cooperation in biotechnology between the scientific communities of India and Germany, the Department of Biotechnology (DBT) will soon begin collaborative research in the identified priority area of 'Bioinformatics in Health Research' under the programme of Indo-German Cooperation in Health Research.

The purpose of the programme is to stimulate new collaborations, e.g. the preparation of joint projects under national funding programmes. The programme facilitates bilateral cooperation in biotechnology between the scientific communities of India and Germany by way of joint research projects which will encompass bilateral workshops/seminar and exchange visits of scientists.

The programme is being implemented within the agreement of Indo-German cooperation in S&T of 1974, under which the Department of Biotechnology, Government of India and Forschungszentrum Julich BMBH (FZJ), Federal Republic of Germany, have agreed for cooperative programme in biotechnology.

DBT of the Ministry of Science & Technology, Government of India and the Project Management Agency at the German Aerospace Center (DLR-PT, European and International Cooperation), Bonn are the nodal implementing agencies from the Indian and German side respectively.

Through this programme, it is expected that the funded cooperation enables the partners to develop applicable scientific results which can be published and/ or could be commercialised and may lead to formation of joint ventures. All publications, patents coming out of these projects, need to be jointly authored by both Indian and German scientists. All necessary approvals like ethical clearance, HMSC approval from Indian point of view as well as EU, if applicable, from German point of view, e.g. before conducting animal experimentation if any needs to be obtained by PIs before undertaking the project.

Now, both the nodal agencies have invited research proposals in identified priority area of 'Bioinformatics in Health Research' from eligible scientists. Joint research projects are required to be submitted to both the nodal agencies by 15 January 2018. Scientists/faculty members working in regular capacity in universities, national R&D laboratories/institutes and private R&D institutes can be part of this joint research programme. For the private sector, partners from all kind of private sectors are eligible, but financing is limited. For Indian scientists from the private sector, only local hospitality in Germany as part of the exchange visit is available from the German side. For German scientists from the private sector, only travel costs are available for small and medium size enterprises (for definition of SME ref. to 2003/361/EC) as well as local hospitality in India will be borne by themselves.

CSA: A high-throughput chromosome-scale assembly pipeline for vertebrate genomes

Jit — Wed, 10 Mar 2021 06:13:49 -0600

The pipeline can use information from scaffolded assemblies (for example from HiC or 10X Genomics), or even from diverged (~65-100 Mya) reference genomes for ordering the contigs and thus support the assembly process. This typically results in improved contig N50 when compared to current state of the art methods.

For smaller vertebrate genomes (~1 Gbp) chromosome scale assemblies can be achieved within 12h on high-end Desktop computers (Intel i7, 12 CPU threads, 128 GB RAM). Larger mammalian genomes (~3Gbp) can be processed within 15-18 h on server equipment (Xeon, 96 CPU threads, 1TB RAM).

Address of the bookmark: https://github.com/HMPNK/CSA2.6

An Introduction to Applied Bioinformatics

Jit — Fri, 02 Mar 2018 04:26:38 -0600

IAB is primarily being developed by Greg Caporaso(GitHub/Twitter: @gregcaporaso) in the Caporaso Lab at Northern Arizona University. You can find information on the courses I teach on my teaching website and information on my research and lab on my lab website.

Address of the bookmark: http://readiab.org/

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

SciLifeLab tutorial for bioinformatics analysis !

Jit — Tue, 17 Apr 2018 04:33:00 -0500

SciLifeLab is a national center for molecular biosciences with focus on health and environmental research.

Courses

Old courses (2012-2014)

odgi: optimized dynamic genome/graph implementation

Abhimanyu Singh — Tue, 01 Feb 2022 23:42:21 -0600

odgi provides an efficient and succinct dynamic DNA sequence graph model, as well as a host of algorithms that allow the use of such graphs in bioinformatic analyses.

Careful encoding of graph entities allows odgi to efficiently compute and transform pangenomes with minimal overheads. odgi implements a dynamic data structure that leveraged multi-core CPUs and can be updated on the fly.

The edges and path steps are recorded as deltas between the current node id and the target node id, where the node id corresponds to the rank in the global array of nodes. Graphs built from biological data sets tend to have local partial order and, when sorted, the deltas be small. This allows them to be compressed with a variable length integer representation, resulting in a small in-memory footprint at the cost of packing and unpacking.

The RAM and computational savings are substantial. In partially ordered regions of the graph, most deltas will require only a single byte.

Address of the bookmark: https://github.com/pangenome/odgi

BOL: Related items

SvABA: Structural variation and indel detection by local assembly

RA Bioinformatics at NATIONAL INSTITUTE OF BIOMEDICAL GENOMICS, INDIA

RefKA: A fast and efficient long-read genome assembly approach for large and complex genomes

Bioinformatics lectures !

India and Germany to begin joint research in the area of 'Bioinformatics in Health Research'

CSA: A high-throughput chromosome-scale assembly pipeline for vertebrate genomes

An Introduction to Applied Bioinformatics

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

SciLifeLab tutorial for bioinformatics analysis !

Courses

Metagenomics Workshop

Introduction to Bioinformatics Using NGS Data

Introduction to Genome Annotation

De Novo Genome Assembly

RNA-seq course

R Programming Foundations for Life Scientists

Single cell RNA sequencing analysis

odgi: optimized dynamic genome/graph implementation