Overview of SLiM and msprime

SLiM: Forward Genetic Simulator

SLiM is a free, open-source tool designed for forward genetic simulations. It allows researchers to model complex evolutionary scenarios, including selection, recombination, and demographic events, making it particularly useful for studying adaptation and selection in populations.

Key Features of SLiM:

• Simulates population evolution forward in time

• Supports custom evolutionary models using an embedded scripting language

• Allows modeling of spatial and ecological dynamics

• Provides high flexibility and extensibility for user-defined scenarios

• Available on GitHub as an open-source project

msprime: Ancestry and Mutation Simulator

msprime is an efficient, open-source tool that simulates ancestry and mutations using a coalescent framework. It is known for its high-speed performance and low memory requirements, making it a popular choice for large-scale genomic simulations.

Key Features of msprime:

• Implements coalescent simulations for ancestry modeling

• Efficiently simulates large population histories

• Supports the addition of mutations to genealogies

• Developed using an open-source community model

• Often faster and more memory-efficient than alternative simulators

Using SLiM and msprime with slendr

Both SLiM and msprime can be integrated with slendr, a framework that facilitates structured population genetic simulations. This integration allows for seamless comparison of simulation outputs.

How They Work Together:

• SLiM and msprime simulations can be analyzed within slendr.

• The ts_read() function in slendr enables loading and comparing tree sequence outputs from both simulators.

• This integration allows researchers to validate simulation results and gain deeper insights into evolutionary processes.

Performance Considerations

While SLiM offers powerful forward simulations with extensive customization, msprime is often preferred for its speed and memory efficiency when simulating ancestry and mutations. The choice between the two depends on the research goals:

• For detailed evolutionary modeling with selection and recombination: Use SLiM.

• For large-scale coalescent simulations with mutations: Use msprime.

• For comparing different simulation models and their outputs: Use slendr to integrate SLiM and msprime results.

Conclusion

SLiM and msprime are valuable tools for genome simulation, each serving distinct but complementary purposes in population genetics research. By leveraging the strengths of both simulators with slendr, researchers can conduct robust and efficient evolutionary simulations, enhancing our understanding of genetic diversity and adaptation.

For more information, check out the official GitHub repositories for SLiM and msprime, and explore the slendr framework for streamlined simulation workflow

Location : Kulu

Job Category : Govt Jobs, Research

Last Date : 20 May 2015

Job Type : Full Time

Hiring Process : Walk - In
IIT Mandi - Job Details
IIT Mandi

Project Associate Bioinformatics Job vacancies in IIT Mandi on purely temporary

Project: “Exploring the Human Microbiome: A hunt for the candidates for Pre- and Pro-biotics.”

Minimum Qualification and Experience: M.Sc. in Bioinformatics OR B.Tech / BE in Bioinformatics OR M. Sc. in Biotechnology / Life sciences or related areas with Diploma or relevant experience in Bioinformatics OR B.Tech in Biotechnology / Computer Science or MCA or B. Sc. in Life Sciences or related areas with PG diploma in Bioinformatics. Candidates with experience in NGS data handling and analysis will be preferred. Tenure: Initially for one year, extendable based upon performance.

No of Posts: 01

Salary: Rs. 12000- 18000/- per month.

How to apply

Interested candidates can come for a Walk-in-Interview on 20th May 2015 starting at 8:30 AM at the Academic Block, Indian Institute of Technology (IIT), Mandi, Vallabh College Campus, Near Bus Stand, Mandi, HP. The candidates should bring along their curriculum vitae (CV) and copies of educational and experience certificates. In case of any queries please contact: Dr. Tulika Prakash Srivastava (Principal Investigator), Indian Institute of Technology Mandi, Near Bus Stand Mandi - 175 001, Himachal Pradesh.

More at

http://www.iitmandi.ac.in/administration/advrt/Walk-in-interview_Ad.pdf

When the query file format is fasta, you can specify many threads to process it. It can reduce run time linearly, and use almost equal memory as the original lastz program. This is useful when you lastz a big query file to a huge reference like human whole genome sequence.

The program is an extension on the original lastz program which was written by Bob Harris (the LASTZ guy).

Address of the bookmark: https://github.com/jnarayan81/parallelLastz

Project Assistant (Level-II) job position in Central Food Technological Research Institute (CFTRI) on a temporary contractual basis in the research project (GAP 0469) funded by Science & Engineering Research Board (SERB), Government of India, New Delhi tenable at the Lipidomics Centre, CSIR-CFTRI, Mysore, Karnataka

Name of the Position :

Qualification : First class M. Sc. in Biochemistry/Microbiology/Genetics/ Bioinformatics with good academic record and preferably with experience in molecular biology techniques and basic knowledge of molecular biology and biological chemistry

Emoluments : Rs. 12,000/- per month (Consolidated)

Age Limit : The upper age limit for applying shall be 28 years (as on 22-5-2015), which is relaxed for candidates belonging to Scheduled Castes/Schedule Tribes, Women, Persons with Disabilities (PWD) and OBCs as per GoI norms.

How to apply

Eligible candidates may send their complete Bio-data with e-mail address/contact phone number along with attested copies of the necessary certificates through post to Prof. Ram Rajasekharan, Lipidomics Centre, Department of Lipid Science, CSIR-CFTRI, Mysore-570 020, Karnataka (email: ram@cftri.res.in) on or before 22.05.2015

More at http://www.cftri.com/pa_gap0469.html

This bookmark is created to provide NGS online books links.

Address of the bookmark: http://en.wikibooks.org/wiki/Next_Generation_Sequencing_%28NGS%29/Print_version

Details will be available at: http://nrcorchids.nic.in/Employments/Vacancy%20-%20JRF.pdf

The work in our lab has focussed on computational approaches to speed-up the finishing process. Specifically, we have explored the use of optical mapping and mate-pair data to augment assemblies and direct finishing experiments. The tools developed in our lab have been used in several finishing projects, producing complete genomes (and near-complete ones) with surprisingly little computational and experimental effort (Nagarajan et al., in submission). The executables (as well as source code) for these tools are freely available here:

• Scaffolding using Optical Restriction Mapping
  Optical Maps are global, ordered maps of restriction site locations in a genome. This information can be quite useful in scaffolding contigs from a shotgun assembly to guide the finishing process. A set of programs to exploit optical maps for assembly can be found here: SOMA v2.0 (63 MB tar.gz file). This version of SOMA contains several improvements to programs in v1.0 as well as new scripts for working with multiple maps, contig graphs and scaffolds. 
  
  
• Augmenting assemblies with mate-pair data
  Mate-pair information can be valuable in augmenting short-read assemblies and reconstructing the genome as larger scaffolds. AMOS-Hybrid is a pipeline written in the AMOS framework (open-source assembly tools) to merge arbitrary mated reads into an existing assembly and merge contigs and create scaffolds where possible. Source code and executables for AMOS-Hybrid are available here: AMOS-Hybrid v1.0 (142 MB tar.gz file). 
  
  
• Assembly and sequence-composition guided finishing
  Contigs from a shotgun assembly are typically linked together in a graph structure that can serve to guide finishing and in some case close gaps in-silico. Also, in many cases, sequence composition of contigs can provide clues to fill gaps in scaffolds. A set of scripts to automate some of these tasks can be found here: Finishing Scripts v1.0 (63 MB tar.gz file). 

http://www.cbcb.umd.edu/finishing/

Address of the bookmark: http://www.cbcb.umd.edu/finishing/

PO Box: 21

DHARAMSHALA, DISTRICT KANGRA, HIMACHAL PRADESH – 176215

EMPLOYMENT NOTICE NO.: 02 / 2015

APPOINTMENT TO VARIOUS TEACHING, NON-TEACHING AND OTHER ACADEMIC STAFF POSITIONS

Applications in the prescribed form are invited from the eligible candidates for the following Teaching, Non-Teaching and other Academic Staff positions to be filled up on regular basis: Details of teaching positions:

15. School of Life Sciences

Computational Biology & Bioinformatics

1 (ST - 1) 2 (UR - 2)

Last Date of receipt of applications: 22ND JUNE, 2015

Advertisement:

http://www.cuhimachal.ac.in/download/2015/may-2015/emp-notice-eng/1.%20Employment%20Notice%20No.%2002-2015%20dated%2019.05.2015_for%20Website.pdf

Relying on unique software architecture, PLAST takes full advantage of recent multi-core personal computers without requiring any additional hardware devices.

PLAST stands for Parallel Local Sequence Alignment Search Tool and is was published in BMC Bioinformatics.

PLAST is a general purpose sequence comparison tool providing the following benefits:

• PLAST is a high-performance sequence comparison tool designed to compare two sets of sequences (query vs. reference),
• Reduces the processing time of sequences comparisons while providing highest quality results,
• Contains a fully integrated data filtering engine capable of selecting relevant hits with user-defined criteria (E-Value, identity, coverage, alignment length, etc.),
• Does not require any additional hardware, since it is a software solution. It is easy to install, cost-effective, takes full advantage of multi-core processors and uses a small RAM footprint,
• Ready to be used on desktop computer, cluster, cloud as well as within distributed system running Hadoop.

https://plast.inria.fr/

Address of the bookmark: https://plast.inria.fr/