• Function(data, options)

Even quit is a function

• q()

So is help

help(read.table)

Provides the help page for the FUNCTION ‘read.table’

help.search(“t test”)

Searches for help pages that might relate to the phrase ‘t test’

NOTE: quotes are needed for search strings, they are not needed when referring to data objects or function names.

There is a short cut for help,

? shows the help page on a function name, same as help(function)

?read.table

?? searches for help pages on functions, same as help.search(‘phrase’)

??“t test”

Information is usually returned from a function, by default this is printed to screen

read.table(‘data.tsv’)

This can always be stored, we call what it is stored in an ‘object’

mydata

here mydata is an object of type dataframe

Reminder:

• Vector: a list of numbers, equivalent to a column in a table
• Data Frame = a collection of vectors. Equivalent to a table

Hint:

• Up/Down arrow keys can be use to cycle through previous commands

Address of the bookmark: https://github.com/legumeinfo/gcv

Central University of Jharkhand has been granted funds by the Department of Biotechnology (DBT), Govt. of India to establish “DBT-Boost to CUJ Interdisciplinary Life Sciences Departments for Education and Research” Applications are invited for the Assistant Professor on purely temporary basis. The appointments shall be initially for a period of one year, renewable every year depending on the satisfactory performance, till the end of project.

Position: ASSISTANT PROFESSOR (Total 03)
Salary: 45,000/- (fixed) per month
Essential Qualifications: i. Good academic record with at least 55% marks (or an equivalent grade in a point scale wherever grading system is followed) at the master’s degree level with specialization in Biodiversity and Systematic/ Systems Biology/ Biophysics/ Bioinformatics from an Indian University, or an equivalent degree from an accredited foreign university. ii. Besides fulfilling the above qualifications, the candidates must have cleared the National Eligibility Test (NET) conducted by the UGC, CSIR or similar test accredited by the UGC like SLET/SET. iii. Notwithstanding anything contained in i. and ii. candidates, who are or have been awarded Ph.D Degree in accordance with the University Grants Commission (Minimum Standards and Procedure for Award of Ph.D. Degree) Regulation, 2009, shall be exempted from therequirement of the minimum eligibility condition of NET/SLET/SET for recruitment and appointment of Assistant Professor. iv. NET/SLET/SET shall also not be required for such disciplines for which NET/SLET/SET in not conducted.
Desirable: Preference will be given to candidates having Ph.D in any of the above mentioned areas with NET

IMPORTANT DATES TO REMEMBER :

Last Date to Apply for this job 24/3/2015

REFERENCE:

Central University of Jharkhand (CUJ) Recruitment 2015 – Advt. No.: CUJ/Advt./14-15/15 Date: 26th Feb. 2015.

More at http://cuj.ac.in/careers.php

Features

• Circular and linear views of genomes

• Capable of drawing genomes up to 10 Mbp with 1000's of features and 100's contigs

• Smooth zooming down to the sequence level

• Easily generate features and plots directly form the sequence (e.g. ORFs, GC-content and GC-Skew)

• Save high resolution PNG maps up to 8000x8000px

• Fully documented API for interacting with CGView.js maps

Address of the bookmark: https://js.cgview.ca/

http://molbiolabccsumrt.webs.com/

Applications are invited for one post of RA in a DBT funded research project “Creation of Bioinformatics Infrastructure Facility (BIF) for the promotion of Biology Teaching through Bioinformatics (BTBI) Scheme of BTISet”.

Candidate should have a Ph.D. degree in Bioinformatics/Biotechnology/Genetics and Plant Breeding with adequate experience in the area of Bioinformatics. If a suitable candidate for the post of RA is not available, a JRF/SRF may be appointed.

Candidate for the post of JRF/SRF should have Master’s degree in relevant subject with adequate experience in the area of Bioinformatics and should be NET/DBT-BINC qualified

Interested candidates may send their bio-data to Prof. H. S. Balyan (hsbalyan@gmail.com) (in exceptional case, bio-data may also be submitted at the time of interview) and attend the interview on Monday, March 30, 2015 at 11:00 AM in the Department of Genetics & Plant Breeding, Ch. Charan Singh University, Meerut. Candidates shall bring their original documents at the time of interview for verification. No interview letters will be issued and no TA/DA will be paid.

What is Genome Assembly?

Genome assembly involves piecing together short DNA sequence reads generated by sequencing platforms (e.g., Illumina, PacBio, Oxford Nanopore) into longer, contiguous sequences called contigs. This can be performed as:

• De Novo Assembly: Without a reference genome.
• Reference-Guided Assembly: Using a reference genome to guide the assembly process.

Step 1: Preparing Your Data

Before starting the assembly, ensure that your raw sequencing data is high quality.

1. Input Data

   • Short Reads: Illumina sequencing generates short, accurate reads ideal for scaffolding.
   • Long Reads: PacBio and Nanopore sequencing provide long reads for resolving repetitive regions.

2. Quality Control (QC)
   Use tools like FastQC or MultiQC to assess the quality of your reads:

   fastqc reads.fastq multiqc .

   Look for issues like low-quality bases, adapter contamination, or overrepresented sequences.

3. Read Trimming and Filtering
   Trim low-quality bases and adapters using Trimmomatic or Cutadapt:

   trimmomatic PE reads_R1.fastq reads_R2.fastq trimmed_R1.fastq trimmed_R2.fastq \ ILLUMINACLIP:adapters.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:20 MINLEN:36

Step 2: Choosing an Assembly Strategy

Select an assembly strategy based on your data type:

• Short-Read Assemblers:

  • SPAdes: Popular for microbial genomes.
  • Velvet: Fast for smaller genomes.

• Long-Read Assemblers:

  • Canu: Ideal for long-read datasets.
  • Flye: Versatile for small and large genomes.

• Hybrid Assemblers:

  • MaSuRCA: Combines short and long reads.
  • Unicycler: Optimized for bacterial genomes.

Step 3: Running the Assembly

3.1. SPAdes (Short-Read Assembly)

SPAdes is an excellent choice for small genomes, such as bacteria.

The output includes assembled contigs (contigs.fasta) and scaffolds (scaffolds.fasta).

3.2. Canu (Long-Read Assembly)

Canu is designed for high-error long reads from PacBio or Nanopore.

The output will be in canu_output/genome.contigs.fasta.

3.3. Hybrid Assembly with Unicycler

Unicycler combines short and long reads for improved assemblies.

Step 4: Assessing Assembly Quality

After assembly, evaluate its quality using the following tools:

1. QUAST
   QUAST generates assembly statistics, such as N50, genome size, and GC content:

   quast contigs.fasta -o quast_output

2. BUSCO
   BUSCO checks genome completeness by identifying conserved genes:

   busco -i contigs.fasta -o busco_output -l fungi_odb10 -m genome

3. Assembly Graph Visualization
   Visualize assembly graphs with Bandage:

   Bandage load assembly_graph.gfa

Step 5: Post-Assembly Steps

1. Polishing
   Improve assembly accuracy using tools like Pilon (for short reads) or Racon (for long reads).

   racon long_reads.fasta mapped_reads.sam contigs.fasta > polished_contigs.fasta

2. Scaffolding
   Link contigs into scaffolds using tools like SSPACE or Opera-LG if required.

3. Annotation
   Annotate the assembled genome using Prokka for prokaryotes or Maker for eukaryotes.

   prokka --outdir annotation_output --prefix genome contigs.fasta

Step 6: Sharing and Archiving

1. Submit to Public Repositories
   Share your assembly in databases like NCBI GenBank, ENA, or DDBJ.

2. Metadata Preparation
   Include detailed metadata for your submission, such as organism name, sequencing platform, and coverage.

Best Practices

• Always perform quality checks at each stage to ensure data integrity.
• Use multiple tools to cross-validate results when working with complex genomes.
• Document parameters and software versions for reproducibility.

Conclusion

Genome assembly is a powerful process that transforms raw sequencing data into a coherent representation of an organism’s genome. By following this step-by-step guide, you can successfully assemble genomes and uncover valuable biological insights. Whether you’re assembling a microbial genome or tackling the complexities of a eukaryotic genome, these tools and strategies will set you on the path to success.

Code in almost all popular languages using Coding Ground. Edit, compile, execute and share your projects, 100% cloud.

http://www.tutorialspoint.com/codingground.htm

Address of the bookmark: http://www.tutorialspoint.com/codingground.htm

Key Findings:

1. Chromosomal Fusion and Its Molecular Signature:

   • The fusion site is located at 2q13–2q14.1 and is characterized by degenerate telomeric sequences appearing interstitially, indicating the historical head-to-head joining of ancestral chromosomes.
   • Despite being a signature of a past fusion event, these telomeric repeats are no longer functional and have undergone sequence degradation over time.

2. Extensive Duplications in the Surrounding Genomic Region:

   • The study identifies large-scale segmental duplications flanking the fusion site, with several of these regions duplicated and scattered across multiple chromosomes.
   • These duplications are predominantly located in subtelomeric and pericentromeric regions, suggesting their role in genomic instability and chromosomal evolution.

3. Paralogous Regions and Their Evolutionary Relationships:

   • A 168-kilobase (kb) segment near the fusion site has 98%–99% sequence identity with three regions on chromosome 9 (9pter, 9p11.2, and 9q13).
   • Another 67-kb region distal to the fusion site shows a high degree of homology to sequences in chromosome 22qter.
   • Additionally, a 100-kb segment exhibits 96% sequence identity with a region in chromosome 2q11.2.

4. Comparative Genomics and Evolutionary Implications:

   • By comparing the duplicated sequences and their arrangement in primates, the researchers traced the order of duplication events leading to their present distribution.
   • The presence of specific repetitive elements within these duplicated segments serves as evolutionary markers that help infer their historical rearrangements.
   • Some of these duplicated regions are associated with chromosomal inversion breakpoints, potentially contributing to evolutionary changes in primates.
   • Recurrent structural rearrangements in these regions have been linked to human chromosomal disorders.

Conclusions and Implications:

• The findings provide valuable insights into the structural evolution of human chromosome 2, which played a crucial role in human speciation.
• Understanding these segmental duplications and their evolutionary trajectories sheds light on genomic instability, which may contribute to human genetic diseases.
• The study highlights how large-scale chromosomal rearrangements, such as fusion and duplication, have influenced the evolutionary divergence of humans from other primates.

This research advances our understanding of human genome evolution and offers a foundation for studying the effects of structural variants in genetic disorders.

DEPARTMENT OF BIOTECHNOLOGY

No. NITW/Bio/ Date: 30th March 2015

ADVERTISEMENT FOR PROJECT FELLOW (Research Staff)

Applications are invited for the post of Project Fellow (Research Staff) for the project entitled ‘Metagenome derived nitroreductases for degradation of nitro compounds’ sponsored by the Department of Science and Technology (DST-INSPIRE), Govt. of India.

Position: Project Fellow (1 No.)

Project Duration: 5 years

Note: The post is purely on temporary basis for a period one year and may be extendable till the end of the project based on the progress of the candidate.

Emoluments: Rs. 14,000/- per month (Consolidated) for first two years and Rs. 16,000/- per month (Consolidated) for next three years.

Essential Qualifications:

i) First class in M.Tech/M.S (Biotechnology/Industrial Biotechnology/Bioinformatics) or equivalent. Or

ii) First class in M.Sc. (Biotechnology/Bioinformatics/Biochemistry/ Microbiology/Molecular biology).

Desirable Qualification: Preference will be given to candidates who have cleared NET/GATE or having prior work experience in Molecular biology/Bioinformatics sequence analysis.

Interested candidates may submit their application in plain paper along with Curriculum Vitae and photocopies of certificates in support of educational/professional qualifications. Application should be sent in a closed cover with a superscription on the cover “Application for the post of project fellow (DST-INSPIRE)” on or before 20.04.2015 (Monday) via Post to the Principal Investigator. Eligible candidates will be intimated through e-mail and called for interview at the Department of Biotechnology, NIT, Warangal. No TA/DA will be paid for attending the interview. Dr. K. Divakar (Principal Investigator) DST-INSPIRE Faculty Department of Biotechnology National Institute of Technology Warangal – 506 004. Telangana, India. E-mail: divakar@nitw.ac.in; kdivak@gmail.com

Advertisement: http://www.nitw.ac.in/nitw/announcements/2015/Notification_Project_Fellow_DST_INSPIRE_Biotechnology_NITW.pdf

The engagement is purely temporary on contractual basis and co-terminus with the project. There will be no provision of absorption of absorption/reemployment in IVRI/DBT on termination of the project.

No TA/DA will be provided for appearing in the interview and no separate letter will be issued.

A. Name tile of the project: “Centre for Agricultural bioinformatics (CABin)”.

B. Position/post to be filled: Research Associate (one)

C. Essential/Desirable qualifications:

•Essential: M.V.Sc./M.Tech./MSc Degree in Biotechnology/ Biochemistry/ Microbiology/Immunology/Bioinformatics/Genetics/Life Sciences or

Masters in Computer Application/ Masters in Computer science with first division.

• Desirable: Experience in cell culture, next generation sequencing, C++ and perl programming. NET/GATE qualified will be preferred.

• Experience : At least 2 years

D. Emoluments: Rs. 23000/- per month + 20% HRA

E. Age Limit: Maximum 40 years for men and 45 years for women

F. Duration of the project: Up to March 2017

G. Name of PI/Contact person: Dr. G.V.P.P.S. Ravi Kumar, Sr. Scientist, Division of Veterinary Biotechnology.

H. Address for correspondence: Dr. G.V.P.P.S. Ravi Kumar, Sr. Scientist, Computational Biology and Genomics facility,Division of Veterinary Biotechnology, I.V.R.I., Izatnagar – 243122

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