Below you can find a few basic tutorials for how to run MITObim and I encorage you to give them a try with the testdata that comes with this Repo, just to make sure everything is running smoothly on your system. It'll only take a few minutes and will potentially safe you a lot of time down the line.

I provide further examples here as Jupyter notebooks. Get in touch if you feel like sharing your particular MITObim solution and I'd be happy to put it up here, too!

Address of the bookmark: https://github.com/chrishah/MITObim

1. Remuneration : Rs. 12000/- per month (consolidated)

2. Qualification : M.Sc./M.Tech. Bioinformatics (preference will be given to the candidates with BINC / NET / GATE / Bioinformatics DBT-Traineeship / Studentship and teaching experience)

3. Place of work : Department of Bioinformatics, SVIMS, Tirupati

4. No. of Position : One

Terms and conditions:

1. Candidates are required to submit the Biodata, attested copies of relevant certificates in support of their age, educational qualification, experience etc., before the interview committee, SVIMS University, Tirupati.
2. No TA / DA will be paid for attending the interview.
3. Interim enquiries will not be entertained.
4. The maximum age limit for Teaching Assistant is 34 years as on 8th August, 2015.
5. The tenure of will be further extended subject to performance of the incumbent.

Advertisement: http://svimsbic.org/Teaching_Assistant_B.I._2015.pdf

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

CPAT - https://github.com/liguowang/cpat, http://lilab.research.bcm.edu/ (web server)

CPC2 - https://github.com/gao-lab/CPC2_standalone, http://cpc2.gao-lab.org/ (web server)

Infernal - http://eddylab.org/infernal/, https://github.com/EddyRivasLab/infernal

NCBI RefSeq - https://www.ncbi.nlm.nih.gov/refseq/

Rfam - http://rfam.xfam.org/, https://docs.rfam.org/en/latest/index.html

SILVA - https://www.arb-silva.de/

RNAmmer - http://www.cbs.dtu.dk/services/RNAmmer/ (web server, standalone download link)

Pondicherry University Puducherry has been identified as a nodal agency by the Department of Biotechnology, Govt. of India to coordinate this examination along with nine centres namely, Pune University, Pune; Anna University, Chennai; Calcatta University (WBUT) Kolkata; Institute of Bioinformatics & Applied Biotechnology, Bangalore; North-Eastern Hill University, Shillong, University of Hyderabad, Hyderabad; University of Kerala, Thiruvananthapuram; Jawaharlal Nehru University, New Delhi and Assam Agricultural University, Guwahati.

In the BINC 2013 examination,17 candidates were certified. DBT has agreed to fund Research fellowships for all the BINC qualified Indian nationals to pursue Ph.D. in Indian Institutes/Universities. Note that the candidate must possess a postgraduate degree(or equivalent) & meet the criteria of the institutes/universities in order to avail research fellowship. In addition, cash prize of Rs. 10,000/- will be awarded to the top 10 BINC qualifiers.

More at http://210.212.230.224:9999/BINC/

Metagenomic simulators are a way of dealing with this issue; they produce artificial sequencing datasets in which both the composition of the microorganisms and the expected results are known. Researchers can then test a pipeline on such a controlled dataset and see precisely how well it functions. However, as metagenomic studies have become larger, more diverse, and more complex, simply generating artificial reads is no longer sufficient. The simulators now have to replicate community variation, sequencing errors, different sequencing platforms, massive data volumes, and even laboratory-based biases.

MIDASim (2024) was designed with a particular emphasis on microbial community dynamics. Unlike previous tools which regarded each simulated sample as individual, MIDASim is able to efficiently generate realistic multi-sample microbiome datasets, covering the cases where changes over time are being tracked. This feature is particularly useful when investigating how microbial communities vary between people, different experimental setups, or at various times. By overcoming the computational limitations of earlier simulation methods, MIDASim has made it easier to carry out large and complex microbiome simulation studies.

A major challenge is scale. Since modern metagenomic projects can involve millions or even billions of sequencing reads, generating such large synthetic datasets can become a significant computational problem. In order to tackle this issue, Izzy (2025) was developed. As a high-throughput metagenomic read simulator, Izzy is designed with speed in mind while still reproducing the typical patterns of sequencing errors. The people who developed it stated that it can be as much as 60 times faster than earlier tools, which makes large-scale simulations far more practical. Now, researchers can begin to ask not how long a simulation will take but rather what size dataset they want to test.

At the same time, the sequencing technology became more diverse. Researchers were not any longer restricted to using Illumina short reads since Oxford Nanopore and PacBio long-read sequencing also became important in the field of metagenomic research. In order to address these new requirements, MeSS (Metagenomic Sequence Simulator, 2025) was developed. The programme is based on a Snakemake framework and is therefore compatible with the Illumina, Oxford Nanopore and PacBio platforms. MeSS has also been designed to operate efficiently and to use less memory than earlier tools; it provides ready-made templates for the microbiomes of different sites in the human body, thus giving researchers a simple means of beginning to generate realistic simulated communities.

The simulation problem became even more specialized. Suppose that sequencing is not based on uniform sampling of DNA? In the case of targeted sequencing and hybridization-capture experiments, particular sequences are deliberately enriched, and the probability of capturing a target depends on both the probe and the target sequence. A standard model based on uniform sampling might fail to take into account this important feature of real experiments. That is why RAmpSim has been designed specifically to handle simulations for capture-based and targeted sequencing. Instead of depending solely on the assumption of uniform sampling, it includes a thermodynamic nearest-neighbor energy model to represent probe–target interactions and sequence-dependent enrichment. As a result, it is especially suitable for applications such as hybridization capture in metagenomics, where the efficiency of recovering a sequence can depend strongly on how it relates to the capture probes. RAmpSim thus reflects a wider trend towards simulations that aim not only to reproduce sequencing output but also key aspects of the experimental process itself.

MIDASim, Izzy, MeSS and RAmpSim all demonstrate how fast metagenomic simulation is evolving. MIDASim is able to deal with realistic variation within a large number of and changing microbial communities. Izzy overcomes the problem of generating very large datasets. MeSS provides support for a number of sequencing technologies in an efficient and repeatable manner. RAmpSim increases the experimental realism for capture-based sequencing. Although each of these tools addresses a separate issue, they all contribute to advancing the field.

Modern metagenomic simulation therefore aims not only at producing artificial FASTQ files. Researchers nowadays desire simulated datasets that reflect community changes, incorporate the characteristics of the sequencing platform, include real error patterns, take into account computational scale, and account for experimental biases. As metagenomic workflows become more advanced, the simulators have to keep up with this development. The tools are now going beyond that of simple data generators; they produce controlled versions of complex metagenomic experiments and thus provide researchers with something that ordinary sequencing data seldom does: a dataset in which the answer is known before any analysis takes place.

Applications with complete bio-data from candidates possessing the required qualifications are invited for the posts of JRF (2) and Project Assistant (1) in

DBT, GOI-funded research project “Next Generation Sequencing (NGS)- based de novo assembly of expressed transcripts and genome information of Orchids in North-East India” in DBT’s Twinning programme for NE as per DBT sanction order and norms.

(i) JRF(2 nos.):

Qualifications: M.Tech/M.Sc in Life Sciences/ Botany/ Zoology/Biochemistry/ Biotechnology/ Bioinformatics; Desirable: Aptitude for Bioinformatics and Computer Programming/ Next generation sequencing data analysis

(ii) Project Assistant (1 no.):

Qualifications: Graduation in Science, Desirable: Experience of working in a Life Science/Plant Biotechnology lab. and familiarity with computers and field work viz. collection of samples.

The applications through email bicnehu@gmail.com or post must reach the undersigned
within 15 days from the date of publication of this advertisement. The advertised posts are purely temporary for the duration of the project and subject to availability of the funds from DBT. The appointment does not confer any entitlement or right over the posts for absorption in the University service.

Advertisement: www.nehu.ac.in/Advertisements/BICAdvtPV_200115.pdf

This package is a loose collection of scripts. To run the correction
routine see the section below. Descriptions of the other scripts
are at the bottom of this file.

Contact: gurtowsk@cshl.edu

In short, the correction algorithm takes as input the unitigs from a short read assembly and uses them to correct long read data. More background information for the algorithm can be found:
http://schatzlab.cshl.edu/presentations/2013-06-18.PBUserMeeting.pdf

Address of the bookmark: https://github.com/jgurtowski/ectools

Organiser: Christine Carrington (University of the West Indies - UWI, St. Augustine, Trinidad and Tobago)
Co-organisers: Anne-Mieke Vandamme, Philippe Lemey (Katholieke Universiteit Leuven, Belgium), Marco Salemi, Mattia Prosperi (University of Florida, Gainesville, USA) and Karen E. Nelson (J. Craig Venter Institute, Rockville, USA)

Requests for information directly to:
Christine Carrington
Department of Preclinical Sciences
Faculty of Medical Sciences
University of the West Indies (UWI)
St. Augustine
Trinidad and Tobago
Telephone: +1-868-6452640 ext. 5009, +1-868-6848803
Fax: +1-868-6621873
E-mail: veme2015@sta.uwi.edu

Deadline for receipt of applications by local organiser: 15 March 2015
CALL FOR APPLICATIONS NOW OPEN
http://www.icgeb.org/course-application-trinidad-and-tobago-2015.html

http://rega.kuleuven.be/cev/veme-workshop/2015