BOL: Related items

ALE: Assembly Likelihood Estimator

BioStar — Wed, 08 Mar 2023 01:39:33 -0600

Just import the assembly, bam and ALE scores. You can convert the .ale file to a set of .wig files with ale2wiggle.py and IGV can read those directly. Depending on your genome size you may want to convert the .wig files to the BigWig format.

Address of the bookmark: https://github.com/sc932/ALE

Steps to find all the repeats in the genome !

Neel — Thu, 31 Aug 2023 02:43:28 -0500

To find repeats in a genome from 2 to 9 length using a Perl script, you can use the RepeatMasker tool with the "--length" option[0]. Here's a step-by-step guide:

Install RepeatMasker: First, you need to install RepeatMasker on your system. You can download it from the RepeatMasker website[0].

Prepare the genome sequence: Make sure you have the genome sequence in a FASTA file format. Let's assume the file is named "genome.fasta".

./RepeatMasker -pa -nolow -norna -no_is -div -lib RepeatMaskerLib.embl -gff -xsmall -small -poly -species -dir -length - genome.fasta

Replace the following placeholders with appropriate values:

: The number of processors/threads you want to use for parallel processing.
: The divergence value for the species you are analyzing. You can find divergence values for different species in the RepeatMasker documentation[0].
: The name of the species you are analyzing.
: The directory where you want the output files to be saved.
and : The minimum and maximum lengths of the repeats you want to find (in this case, 2 and 9).

Analyze the output: RepeatMasker will generate several output files, including a .out file. You can parse this file to extract the information you need. There is a Perl tool called "one_code_to_find_them_all.pl" that can help you parse RepeatMasker output files[0]. You can download it from the source provided.

Use the provided Perl script: Once you have the "one_code_to_find_them_all.pl" script, you can run it to conveniently parse the RepeatMasker output files. Here's an example of how to use it:

perl one_code_to_find_them_all.pl --rm --length

Replace with the path to your RepeatMasker .out file, and with the path to a file containing the lengths of the reference elements.

This script will generate several output files, including .log.txt and .copynumber.csv, which contain quantitative information about the identified repeat elements.

Remember to adjust the parameters and options according to your specific needs and the characteristics of your genome.

Appointment of two traineeships and two studentships in Bioinformatics

Fri, 08 May 2015 00:24:20 -0500

Applications are invited for the appointment of two traineeships and two studentships in Bioinformatics for a period of six months sponsored by Department of Biotechnology, Government of India in the Bioinformatics Sub-DIC, Saraswathy Thangavelu Centre, JNTBGRI, Puthenthope, Thiruvananthapuram 695 586. The required qualifications and other details are given below.

Position 1: Traineeship
Monthly fellowship (in rupee): 5,000/-
No. of vacancies: Two
Required Qualification: First Class M.Sc Bioinformatics/ Biotechnology/ Botany

Position 2: Studentship
Monthly fellowship (in rupee): 5,000/-
No. of vacancies: Two
Required Qualification: M.Phil/M.Tech Bioinformatics/ Biotechnology/ any branch of Life Science students for doing their thesis work in the area of Bioinformatics.

Age limit as on 1.1.2015, 28 years. Age relaxation will be provided for SC, ST, OBC candidates as per Govt. norms.

Interested candidates may appear for walk-in-interview on 15th May 2015 at 10.30 am at JNTBGRI, Palode, Thiruvananthapuram. The candidate should report to the Office at Palode before 10.00 am.

More at http://jntbgri.res.in/news/appointment-of-two-traineeships-and-two-studentships-in-bioinformatics/

Tools to access the quality of your assembled genome !

LEGE — Thu, 08 Aug 2024 23:31:18 -0500

FASTA VALIDATOR + SEQKIT RMDUP: FASTA validation
GENOMETOOLS GT GFF3VALIDATOR: GFF3 validation
ASSEMBLATHON STATS: Assembly statistics
GENOMETOOLS GT STAT: Annotation statistics
NCBI FCS ADAPTOR: Adaptor contamination pass/fail
NCBI FCS GX: Foreign organism contamination pass/fail
BUSCO: Gene-space completeness estimation
TIDK: Telomere repeat identification
LAI: Continuity of repetitive sequences
KRAKEN2: Taxonomy classification
HIC CONTACT MAP: Alignment and visualisation of HiC data
MUMMER → CIRCOS + DOTPLOT & MINIMAP2 → PLOTSR: Synteny analysis
MERQURY: K-mer completeness, consensus quality and phasing assessment

Narcis Fernandez-Fuentes Lab

Mon, 25 May 2015 07:30:00 -0500

Welcome to our web-site compiling all the research-related activities of the group. Our research interests relate to a number of areas within Bioinformatics. We have a long-standing interest in protein structure prediction and structure-to-function relationships. We work in the study of biomolecular interactions, modeling of protein complexes, the study and characterization of protein-protein interactions, peptide design, modeling of genetic variation, structure-based protein design and different aspects of Plant Bioinformatics. Take a look at the our databases and servers and the list of publications for more information.

More at http://www.bioinsilico.org/

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

Genomic Scientist at UDSC

Thu, 28 May 2015 19:14:23 -0500

Centre for Genetic Manipulation of Crop Plants

Department of Genetics

University of Delhi South Campus

NEW DELHI – 110 021

WALK-IN-INTERVIEW FOR THE TEMPORARY POSITIONS OF RESEACH SCIENTIT & LAB / FIELD ATTENDANT

1 Research Scientist (RS) – 3

DBT, Ph. D.

Experience on DNA Markers, plant genome mapping and bioinformatics

Salary: 60,000 (Consolidated) + 5% annual increment

Date and time: 25.06.2015 at 10:30 AM

These temporary positions have been sanctioned in a DBT funded project for the Phase II on ‘Centre of Excellence on genome mapping and molecular breeding of Brassicas.’

The applicants are requested to register their names on the day of interview in the First Floor, Biotech Centre, Centre for Genetic Manipulation of Crop Plants, Department of Genetics before the stipulated time for the interview. Only the registered eligible candidates will be interviewed on the day in the Committee Room.

Applicants are requested to bring all related documents, in original and a set of photocopy, for verification.

No TA/DA will be paid for attending the interview.

www.du.ac.in/du/index.php?mact=News,cntnt01,detail,0&cntnt01articleid=5492&cntnt01returnid=83

Does anyone have Nanopore latest updates?

Poonam Mahapatra — Mon, 12 Aug 2013 12:19:29 -0500

There was a lot of buzz about Oxford Nanopore Technologies® is developing the GridION™ system and miniaturised MinION™ device. These are a new generation of electronic molecular analysis system for use in scientific research, personalised medicine, crop science, security/defence and more. The platform technology uses nanopores to analyse single molecules including DNA/RNA and proteins. With a broad patent portfolio, the Oxford Nanopore pipeline includes biological nanopores and solid-state nanopores.

Is this available, or still under trial mode?

https://www.nanoporetech.com/

https://www.nanoporetech.com/technology/the-minion-device-a-miniaturised-sensing-system/the-minion-device-a-miniaturised-sensing-system

Walk-ins for JRF ans SRF post in Assam Agricultural University

Thu, 28 May 2015 19:16:47 -0500

Distributed Information Centre
Department of Agricultural Biotechnology
Assam Agricultural University
Jorhat – 785 013
Walk-in interview

(ABT/DIC/01/2014 (No. AAU/ABT/DIT/Advt. 01/2015/111 Dtd. 19-05-2015)

Walk in interview for the following position will be held on 6th June, 2015 at 10.00AM in the Office Chamber of the undersigned. Candidates may appear for the interview with bio-data, reprints / publication / thesis etc and passport size photographs, original and attested copies of all testimonials etc, which must be presented at the time of interview. The applicants may submit their resume in advance tomkmodi@aau.ac.in.

Research Associate

Ph.D. in Biotechnology/ Bioinformatics. Or

Masters degree in Biotechnology/Bioinformatics with minimum 3(three) years research experience

Desirable : Experience in Bioinformatics as evidenced from published research

Rs 36,000+HRA for the 1st two years and 38,000+HRA for the 3rd year.

Senior Research Fellow

Master Degree in Biotechnology/ Bioinformatics. With 2 (two) years Experience in Bioinformatics as evidenced from Course work/ Diploma/Published research

Rs 28,000+HRA for NET qualified candidate/Professional degree holder

Rs 18,000+HRA for non-NET qualified general degree holder

Junior Research Fellow

Master Degree in Biotechnology/ Bioinformatics/Computer Science/Computer Application

Desirable: Experience in Bioinformatics as evident from Course work/ Diploma/Published research

Rs 25,000+HRA for NET qualified candidate/Professional degree holder

Rs 16,000+HRA for non-NET qualified general degree holder

Note: Term and conditions will be as per the DBT, Govt of India guidelines.

Advertisement: http://14.139.222.145/classified/biotech46.html

A powerful, yet simple, gene set analysis tool for interpreting RNA-seq and NGS results.

Shani — Thu, 30 Oct 2014 09:19:29 -0500

LifeMap Sciences is introducing GeneAnalytics, our new gene set analysis tool, which is applicable for NGS results and differentially expressed gene lists from variable sources. GeneAnalytics provides gene associations with tissues & cells, diseases, pathways, GO terms and compounds.

Our main advantages over other similar tools are:

GeneAnalytics is very simple and intuitive to use.
GeneAnalytics is based on our proprietary databases – GeneCards, MalaCards, PathCards and LifeMap Discovery, each of them integrates information from a very large number of resources.
GeneAnalytics supplies links for extensive background information on each of the matched results.

I invite you to try it out for free at geneanalytics.genecards.org, and would be happy to hear your comments and thoughts on how we can improve.

Yours,

Shani Ben-Ari Fuchs

LifeMap Sciences Team