• DNA-mapping*
• ChIP-seq*
• RNA-seq*
• ATAC-seq*
• scRNA-seq
• Hi-C
• Whole Genome Bisulfite Seq/WGBS

(*Also available in "allele-specific" mode)

snakePipes can be installed via conda :

'conda install -c mpi-ie -c bioconda -c conda-forge snakePipes'.

Source code (https://github.com/maxplanck-ie/snakepipes) and documentation (https://snakepipes.readthedocs.io/en/latest/) are available online.

Address of the bookmark: https://github.com/maxplanck-ie/snakepipes

Applications are invited for the posts of one Junior Research Fellow in the DBT funded project entitled “Plant parasitic nematode genome informatics - insilico resource development”. The project is for a period of three years.

Essential qualifications for JRF: First class M. Sc. / M. Tech in Bioinformatics. Knowledge of programming language, pearl, Statistics and database – HTML, CSS, Java script.

Desirable qualifications: Experience in handling next generation sequencing data

Age limit: 35 years maximum (5 year relaxation for SC/ST and women candidates) Emoluments: 16,000 + 30% HRA.

The post is purely temporary in nature and is co-terminus with the project. The appointment would be initially for one year and may be extended further upon satisfactory performance.

Those who are interested in pursuing Ph.D with strong research aptitude are preferred.

Interested candidates may attend the Walk in interview on 25th March 2014 along with the duly filled application forms (format in the following page) with all the relevant documents.

Venue: Division of Nematology, Indian Agricultural Research Institute, New Delhi 110012 (Room No. 306, 3rd floor, LBS building)

Reporting Time: Interested candidates should report strictly between 10.00 to 10.30 AM.

Interview time: 10.30 AM

Short-listed candidates will be called for interview at New Delhi. However, no TA and DA will be paid for attending the interview.

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gapFinisher can fill gaps in draft genomes quickly and reliably.

Address of the bookmark: https://github.com/kammoji/gapFinisher

is a state-funded virtual research center aimed at promoting imaging and informatics research infrastructure in South Dakota. BioSNTR research foci include analysis of large-scale genomics and imaging data, application of novel microscopy technologies to study signaling pathways, and identification of new compounds to manipulate signaling pathways.
Responsibilities: This person will be part of Plant Science team with research focus in bioinformatic and molecular network analyses of high throughput data (transcriptomic, proteomic, metabolomics, miRNA). The individual will be integrated into functional genomic projects encompassing grapevine dormancy and freezing tolerance (Fennell) and regulation of soybean nodulation (Subramanian). The successful candidate will perform computational analysis of high throughput, next-generation sequence data and possess the ability to use bioinformatics analytical tools on HPC clusters.

Required Qualifications:
• Ph.D. in plant computational biology or bioinformatics.
• Experience in a high performance computing environment.
• Perl, Python and Java programming experience
• Data management and database development experience

Desired Qualifications:
• Parallel computing experience
• Experience working in a multidisciplinary environment

Contact Information
South Dakota State University
Plant Science
Anne Fennell
anne.fennell@sdstate.edu
Tel. Number: 605-688-6373
http://www.biosntr.org

Parliament2 runs a combination of tools to generate structural variant calls on whole-genome sequencing data. It can run the following callers: Breakdancer, Breakseq2, CNVnator, Delly2, Manta, and Lumpy. Because of synergies in how the programs use computational resources, these are all run in parallel. Parliament2 will produce the outputs of each of the tools for subsequent investigation.

Address of the bookmark: https://github.com/dnanexus/parliament2

In our day to day research activity, we need to securely copy our data from several to local computer and visa-versa. I am jotting down some of the commonly used SCP command for your future help. Hope you all will like it

What is Secure Copy?

scp allows files to be copied to, from, or between different hosts. It uses ssh for data transfer and provides the same authentication and same level of security as ssh.

Examples

Copy the file "gene.txt" from a remote host to the local host

    $ scp your_username@remotehost.edu:gene.txt /some/local/directory

Copy the file "foobar.txt" from the local host to a remote host

    $ scp gene.txt your_username@remotehost.edu:/some/remote/directory

Copy the directory "chromosome" from the local host to a remote host's directory "bar"

    $ scp -r chromosome your_username@remotehost.edu:/some/remote/directory/bar

Copy the file "gene.txt" from remote host "rh1.edu" to remote host "rh2.edu"

    $ scp your_username@rh1.edu:/some/remote/directory/gene.txt \
    your_username@rh2.edu:/some/remote/directory/

Copying the files "gene.txt" and "cancer.txt" from the local host to your home directory on the remote host

    $ scp gene.txt cancer.txt your_username@remotehost.edu:~

Copy the file "gene.txt" from the local host to a remote host using port 2264

    $ scp -P 2264 gene.txt your_username@remotehost.edu:/some/remote/directory

Copy multiple files from the remote host to your current directory on the local host

    $ scp your_username@remotehost.edu:/some/remote/directory/\{a,b,c\} .

    $ scp your_username@remotehost.edu:~/\{gene.txt,cancer.txt\} .

scp Performance

By default scp uses the Triple-DES cipher to encrypt the data being sent. Using the Blowfish cipher has been shown to increase speed. This can be done by using option -c blowfish in the command line.

    $ scp -c blowfish some_file your_username@remotehost.edu:~

It is often suggested that the -C option for compression should also be used to increase speed. The effect of compression, however, will only significantly increase speed if your connection is very slow. Otherwise it may just be adding extra burden to the CPU. An example of using blowfish and compression:

    $ scp -c blowfish -C local_file your_username@remotehost.edu:~

Project Scientist-I
Experimental / Computation analysis experience in highthroughput genomics/ clinical application.

Project Manager
Experience in handling large biological projects involving high-throughput genomics/ clinical application.

Scientific Administrative Assistant
Lab Work.

More at https://vinodscaria.genomes.in/positionsopen

We are looking for a motivated candidate for handling proteomic and/or transcriptomic and other data with a strong background in bioinformatics tools and database development. The project will include identification of novel peptides from mass spectrometry-based proteomic data.

Familiarity with statistical tools or wet lab experience will be an added advantage. The position is open for immediate appointment and available for two years. The applicant will be appointed as Research Associate or Senior Research Fellow based on qualifications as detailed below:

Research Associate: Ph.D. in Biological Science or Bioinformatics with relevant publications in peer reviewed journals. Familiarity with bioinformatics tools, database development, programming skills and proteomic and/or other omics data analysis. Salary will be as per ICMR rules and guidelines.

Senior Research Fellow: M.Sc./B.Tech. in any branch of biology/ biotechnology/bioinformatics, with minimum 2 years of research experience (essential). Familiarity with bioinformatics tools, database development, programming skills and proteomic data analysis. Salary will be as per ICMR rules and guidelines.

Application will be shortlisted based on CV, reference letters from mentors and telephonic interview. Candidates will be called for a personal interview at Bangalore before appointment. No travel expense will be provided for attending interview at Bangalore.

Interested candidates may send a Letter of Interest and CV by email to: ravi@ibioinformatics.org on or before May 15th, 2014.

Contact:
Dr. Ravi Sirdeshmukh
Distinguished Scientist & Associate Director, IOB,
Principal Advisor MSMC/MSCTR

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The "Ifs" of NGS QC and Trimming

1. Ensures Data Integrity
   If you want to minimize errors in downstream analyses, QC and trimming remove low-quality reads and bases, ensuring high-confidence data. This step is essential for reliable variant calling, assembly, and other applications.

2. Removes Contaminants
   If adapter sequences or contaminants are present in the raw reads, trimming can eliminate them. This prevents issues like misalignment or incorrect biological interpretations, ensuring cleaner data for analysis.

3. Improves Mapping and Assembly
   If your goal is better alignment to a reference genome or improved de novo assembly, trimming low-quality bases and adapters is critical. High-quality reads map more efficiently and generate more accurate assemblies.

4. Reduces Computational Load
   If you want to save computational resources, trimming reduces the dataset size, which speeds up processing and analysis. Clean datasets mean less computational time spent on processing low-quality data.

5. Prepares for Standardized Analyses
   If your project involves multiple datasets, QC and trimming ensure uniformity across them. This standardization makes comparisons valid and reproducible, particularly in large collaborative studies.

The "Buts" of NGS QC and Trimming

1. Risk of Over-Trimming
   But excessive trimming can lead to the loss of informative sequences, reducing read depth and potentially discarding biologically relevant data. This is especially critical in studies with limited sequencing depth.

2. Bias Introduction
   But trimming algorithms might introduce biases, especially if they inadvertently remove sequences with specific biological patterns. This can skew results and compromise biological insights.

3. Loss of Context in Paired-End Reads
   But trimming one read in a pair more than the other can lead to loss of pairing information. This complicates downstream analyses that rely on paired-end data, such as structural variant detection.

4. Time and Resource Intensive
   But running QC and trimming for large datasets can be computationally expensive and time-consuming. As sequencing depth increases, preprocessing becomes a bottleneck in the analysis pipeline.

5. Variable Standards
   But the criteria for trimming (e.g., quality threshold, minimum read length) can vary between tools and datasets. This variability may affect reproducibility and comparability of results across studies.

Balancing the "Ifs" and "Buts"

To maximize the benefits of QC and trimming while mitigating the challenges, consider the following best practices:

• Use QC Tools Wisely: Start with tools like FastQC to identify quality issues in your raw data. Visualizing quality metrics helps tailor your trimming parameters.

• Choose Reliable Trimming Tools: Tools like Trimmomatic, Cutadapt, and BBduk offer adaptive and customizable trimming options. Select one that aligns with your dataset and project goals.

• Set Reasonable Parameters: Avoid over-trimming by setting quality thresholds and minimum read lengths that balance data retention and quality improvement.

• Test Downstream Effects: Validate the impact of QC and trimming on downstream analyses, such as alignment efficiency, variant calling accuracy, or assembly quality.

• Document Your Workflow: Maintain detailed records of the parameters and tools used for QC and trimming. This ensures reproducibility and enables better troubleshooting.

Conclusion

NGS quality control and trimming are essential steps to ensure reliable and accurate data for analysis. While the "ifs" highlight the clear benefits of these steps, the "buts" remind us of the potential pitfalls. By adopting best practices and carefully balancing these considerations, you can optimize your preprocessing workflow and unlock the full potential of your sequencing data.

(A) Senior Research Fellow (One Post): Emoluments as per DST/DBT norms.

Candidates having M.Sc. degree (with minimum of 55% marks) or equivalent in Life Sciences/Biotechnology/Bioinformatics/ Molecular Biology or any other related field with minimum of two years of post M.Sc. research experience are eligible to apply. The candidate having computer skill (Linux, Perl, Java, MySQL) and/or experience in advanced molecular biology, next generation sequencing data analysis and molecular markers analysis will be preferred.

The position is completely on temporary basis and co-terminus with the project. The initial appointment will be for one year, which can be curtailed/extended on the basis of assessment of the candidate’s performance and discretion of the Competent Authority. NIPGR reserves the right to select the candidate against the above posts depending upon the qualifications and experience of the candidates. Reservation of posts shall be as per Govt. of India norms.

Eligible candidates may apply by sending hard copy of completed application in the given format with a cover letter showing interest and attested copies of the certificates and proof of research experience. The applications should reach at the address given below within 15 days from the date of the advertisement. The subject line on envelope must be superscribed by “Application for the Post of SRF in DST - AISRF project”.

Note: ONLY hard copy of the application in the given format will be accepted.

Last date April 03, 2014

Dr. Mukesh Jain
Staff Scientist
National Institute of Plant Genome Research
Aruna Asaf Ali Marg, P.O. Box NO. 10531,
New Delhi - 110067

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