BOL: Related items

Genome Simulation with SLiM and msprime

BioStar — Fri, 31 Jan 2025 12:47:43 -0600

Genome simulation is an essential tool in population genetics, enabling researchers to model evolutionary processes and study genetic variation. Two widely used simulation tools in this field are SLiM and msprime. While both serve different purposes, they can be used together with the slendr framework to compare simulation outputs effectively.

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

Project Associate Bioinformatics @ IIT Mandi

Wed, 06 May 2015 06:18:47 -0500

Eligibility : MSc(Bio-Informatics, Bio-Tech), BSc, BE/B.Tech(Bio-Medical /Bio-Technology Engg, CSE)

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

sankeyNetwork with networkD3

Jit — Fri, 06 Apr 2018 12:07:55 -0500

You can also create Sankey diagrams with sankeyNetwork. Here is an example using downloaded JSON data:

https://en.wikipedia.org/wiki/Sankey_diagram

Address of the bookmark: https://christophergandrud.github.io/networkD3/#sankey

Project Associate Bioinformatics @ Central Food Technological Research Institute (CFTRI)

Tue, 19 May 2015 07:01:12 -0500

Central Food Technological Research Institute (CFTRI)

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

vcfR: a package to manipulate and visualize VCF data in R

Jit — Thu, 25 Oct 2018 09:05:59 -0500

VcfR is an R package intended to allow easy manipulation and visualization of variant call format (VCF) data. Functions are provided to rapidly read from and write to VCF files. Once VCF data is read into R a parser function extracts matrices from the VCF data for use with typical R functions. This information can then be used for quality control or other purposes. Additional functions provide visualization of genomic data. Once processing is complete data may be written to a VCF file or converted into other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between VCF data and the R environment connecting familiar software with genomic data.

Address of the bookmark: https://github.com/knausb/vcfR

NRCO Vacancies For Junior Research Fellow – Pakyong, Sikkim

Thu, 28 May 2015 19:10:07 -0500

Junior Research Fellow
Pay Scale:Rs 25,000/-
Educational Requirements:MSc (with NET qualification) / M.Tech degree (with or without NET) with minimum 55% marks in Biotechnology/ Bioinformatics/ Molecular Biology or any other related field.
Other Qualification:Computer Skills (Linux, Perl, Java, MySQL) with experience in advanced molecular Biology techniques.
No of Post: 01
How To Apply: Walk-in-Interviews will be held at ICAR-National Research Centre for Orchids,Pakyong 737106, Sikkim for the post of 01 (One) Junior Research Fellow and 01 (One) Project Attendant under Project ‘DBT’s Twinning programme for the NE’ titled “Assessment of chemical and genetic divergence of some fragrant orchids of north-east India for sustainable improvement of community livelihood” as indicated below. The appointment will be on contractual basis and the incumbents shall not have any claim for regular appointment in ICAR.

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

tinycov: standalone command line utility written in python to plot coverage from a BAM file

Jit — Mon, 23 Mar 2020 06:22:08 -0500

Tinycov is a small standalone command line utility written in python to plot the coverage of a BAM file quickly. This software was inspired by Matt Edwards' genome coverage plotter.

To install the stable version: pip3 install --user tinycov

To install the development version:

git clone https://github.com/cmdoret/tinycov.git
cd tinycov
pip install .

Address of the bookmark: https://github.com/cmdoret/tinycov

Tools for Geospatial data analysis !

BioStar — Wed, 22 Mar 2023 02:10:28 -0500

Geospatial data is becoming increasingly important in many fields, including urban planning, environmental science, public health, and more. These tools can help you work with data from a variety of sources, including satellite imagery, GPS data, and other forms of spatial data. They can help you visualize data, perform complex analysis, and even create maps and other visualizations.

The list includes some of the most popular and widely used geospatial tools available in Python. These tools can help you work with data from a variety of sources and in a variety of formats. Some of the tools are focused on visualization, such as Cartopy, Folium, and Contextily, which allow you to create interactive maps and other visualizations. Other tools are more focused on data manipulation and analysis, such as Fiona, GeoPandas, and Rasterio, which allow you to manipulate and analyze spatial data in a variety of ways.

The list also includes some tools for working with specific types of geospatial data. For example, the H3 library is designed specifically for working with hexagonal grids, while PySAL is focused on spatial econometrics and spatial analysis. Whether you are a data scientist, GIS specialist, or geospatial enthusiast, these tools are sure to enhance your work and help you achieve your goals.

In summary, this list is an excellent resource for anyone working with geospatial data in Python. It contains a wide range of tools for working with different types of data, and can help you visualize data, perform complex analysis, and create maps and other visualizations. If you're looking to enhance your skills in geospatial analysis, this list is definitely worth checking out.

These tools are:

ArcGIS - https://lnkd.in/dgC6sKJH
Cartopy - https://lnkd.in/dc8ijXRg
Contextily - https://lnkd.in/dTdQsmKX
Descartes - https://lnkd.in/dCJykxwW
Fiona - https://lnkd.in/d8sJ3Q5a
Folium - https://lnkd.in/dfSsE-MB
GDAL - https://lnkd.in/dYBJBaAY
Geohash - https://lnkd.in/d_NxJ4_M
GeoJSON - https://lnkd.in/daGs2WYq
GeoPandas - https://lnkd.in/dBTFKKV3
Geopy - https://lnkd.in/dfAzR8Xa
Gevent - http://www.gevent.org
H3 - https://h3geo.org/docs/
OSMnx - https://lnkd.in/dm3pHgUS
PyQGIS - https://lnkd.in/dShWyWVr
PySAL - https://pysal.org
Pydeck - https://lnkd.in/dGBFu-iw
Pyproj - https://lnkd.in/dNG9fdkm
RTree - https://lnkd.in/dURMiYpU
Rasterio - https://lnkd.in/dEMC6ve6
Scikit-mobility - https://lnkd.in/dpHhaX2J
Shapely - https://lnkd.in/d568datK

These tools offer a wide range of capabilities for working with geospatial data, from visualizing and manipulating data to performing complex analysis and modeling. Whether you are a data scientist, GIS specialist, or geospatial enthusiast, these tools are sure to enhance your work and help you achieve your goals.

Assistant Professor, Central University of Himachal Pradesh, India

Thu, 28 May 2015 19:22:49 -0500

Central University of Himachal Pradesh

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

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

orthodotter: Synteny plots (oxford grid)

Jit — Wed, 09 Aug 2017 07:16:16 -0500

orthodotter -h
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orthodotter - Plot orthologous genes on an oxford grid.
       -f      : input file, containing orthologous genes, default is stdin
                       species chr-name start end species chr-name start end
       -toPlot  : give the x and y sets and the color separated by double-dots,
                       for example set1:set2:red will plot set1 on x, set2 on y with
                       red points. Could give several -toPlot arguments.
                       To launch the clustering of dots, use extra-option 1=dist,min_nb_genes
                       where dist is the minimal distance (euclidian) between two points and min_nb_genes the minimal
                       number of genes in a cluster to be valid.
       -o      : output file, default is stdout
       -x       : resolution of x axis, default is 600
       -y       : resolution on y axis, default is 600
       -r       : radius of circle representing orthologous genes
       -format       : could be png, gif, jpg, pdf or ps. Default is png.
       -fg           : foreground color, default is black
       -bg           : background color, default is transparent
       -fSize   : fontSize, default is 1
       -filter       : check chromosome names
       -h            : help
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orthodotter -f Vigne_Banane.ortho -toPlot Vigne:Banane:black:1=10,5 -x 1200 -y 1200 -bg white -o Vigne_vs_Banane.png > Vigne_vs_Banane.clusters
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Address of the bookmark: https://github.com/institut-de-genomique/orthodotter