BOL: Related items

Heap: a highly sensitive and accurate SNP detection tool for low-coverage high-throughput sequencing data

Jit — Thu, 19 Apr 2018 08:06:03 -0500

Heap, that enables robustly sensitive and accurate calling of SNPs, particularly with a low coverage NGS data, which must be aligned to the reference genome sequences in advance. To reduce false positive SNPs, Heap determines genotypes and calls SNPs at each site except for sites at the both end of reads or containing a minor allele supported by only one read. Performance comparison with existing tools showed that Heap achieved the highest F-scores with low coverage (7X) restriction-site associated DNA sequencing reads of sorghum and rice individuals. This will facilitate cost-effective GWAS and GP studies in this NGS era. Code and documentation of Heap are freely available from https://github.com/meiji-bioinf/heap and our web site (http://bioinf.mind.meiji.ac.jp/lab/en/tools.html).

Address of the bookmark: https://github.com/meiji-bioinf/heap

gSearch: a fast and flexible general search tool for whole-genome sequencing

Jit — Mon, 06 Aug 2018 17:19:15 -0500

gSearch compares sequence variants in the Genome Variation Format (GVF) or Variant Call Format (VCF) with a pre-compiled annotation or with variants in other genomes. Its search algorithms are subsequently optimized and implemented in a multi-threaded manner.

Address of the bookmark: http://ml.ssu.ac.kr/gSearch/index.html

Indexcov: fast coverage quality control for whole-genome sequencing

Jit — Wed, 29 Aug 2018 09:20:46 -0500

indexcov, an efficient estimator of whole-genome sequencing coverage to rapidly identify samples with aberrant coverage profiles, reveal large-scale chromosomal anomalies, recognize potential batch effects, and infer the sex of a sample. Indexcov is available at https://github.com/brentp/goleft under the MIT license.

Address of the bookmark: https://github.com/brentp/goleft

VariantBam: Filtering and profiling of next-generational sequencing data using region-specific rules

Rahul Nayak — Thu, 04 Oct 2018 16:30:44 -0500

VariantBam is a tool to extract/count specific sets of sequencing reads from next-generational sequencing files. To save money, disk space and I/O, one may not want to store an entire BAM on disk. In many cases, it would be more efficient to store only those read-pairs or reads who intersect some region around the variant locations. Alternatively, if your scientific question is focused on only one aspect of the data (e.g. breakpoints), many reads can be removed without losing the information relevant to the problem.

Address of the bookmark: https://github.com/broadinstitute/VariantBam

NanoPack: visualizing and processing long-read sequencing data

Jit — Tue, 25 Dec 2018 21:20:50 -0600

The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools.

Address of the bookmark: https://github.com/wdecoster/nanopack

jackalope: A swift, versatile phylogenomic and high-throughput sequencing simulator

Abhimanyu Singh — Fri, 26 Jul 2019 00:58:12 -0500

jackalope simply and efficiently simulates (i) variants from reference genomes and (ii) reads from both Illumina and Pacific Biosciences (PacBio) platforms. It can either read reference genomes from FASTA files or simulate new ones. Genomic variants can be simulated using summary statistics, phylogenies, Variant Call Format (VCF) files, and coalescent simulations—the latter of which can include selection, recombination, and demographic fluctuations. jackalope can simulate single, paired-end, or mate-pair Illumina reads, as well as reads from Pacific Biosciences These simulations include sequencing errors, mapping qualities, multiplexing, and optical/PCR duplicates. All outputs can be written to standard file formats.

A swift, versatile phylogenomic and high-throughput sequencing simulator https://jackalope.lucasnell.com

Address of the bookmark: https://github.com/lucasnell/jackalope

PhD position in Translational Medicine

Sat, 15 Feb 2020 06:07:19 -0600

https://www.jobvector.de/jobs-stellenangebote/biologie-life-sciences/wissenschaftliche-r-mitarbeiter-in/phd-position-translational-medicine-129981.html?suid=1b510358c7578e8f75cf04a464fc21a404a574ca

Essential experience / qualifications:
Master / Diploma in Biology, Biochemistry, Molecular Medicine or similar; solid knowledge of molecular and cell biological techniques; good English knowledge

Applications:
Please send your application (including CV, letter of motivation, contact information of two references, and list of publication) by 13.03.2020 at the latest to:

Universitätsklinikum Erlangen
Chirurgische Klinik
Translational Research Center
Prof. Dr. rer. nat. Michael Stürzl
Schwabachanlage 12
91054 Erlangen
E-Mail: michael.stuerzl@uk-erlangen.de

Ktrim: an extra-fast and accurate adapter- and quality-trimmer for sequencing data

Jit — Thu, 11 Feb 2021 21:39:05 -0600

Ktrim is written in C++ for GNU Linux/Unix platforms. After uncompressing the source package, you can find an executable file ktrim under bin/ directory compiled using g++ v4.8.5 and linked with libz v1.2.7 for Linux x86_64 system. If you could not run it (which is usually caused by low version of libc++ or libz library) or you want to build a version optimized for your system, you can re-compile the programs:

user@linux$ make clean && make

Address of the bookmark: https://github.com/hellosunking/Ktrim

Understand Social Media Importance for Researchers With Benefits to the Strategy !

Rahul Nayak — Tue, 14 Jan 2020 23:21:11 -0600

Why have so many researchers embraced Facebook or Instagram pages? They understand the importance of social media and how it adds value. Now that consumers often experience interactions with companies that are not face-to-face, shifting to social media has become an ideal way to actively engage with researchers.

With social media, you have the opportunity to highlight all the best aspects of your research with one click. What information would be most useful for your potential and current research lab to have easy access to?

Don’t leave this vital question unanswered! Social media’s importance is seen when you realize your social pages become a hub for users to easily find out more about your research and what you care about, without clicking away from the app or website they’re already browsing.

You can use social media as a platform to distinguish your research from competing labs, too. Showing researchers that your research personality is clearly defined and consistent is valuable, but you also want to make sure you are also wrapping your research identity in with common trends on the internet (as appropriate) to show your alike researchers that you are up-to-date on the world around you.

Remember, you don’t want to sound inauthentic! Understanding the importance of social media and investing in it gives you the ability to show that you can connect on a personal level with your alike researchers.

The importance of social media is seen in that it provides value while also creating a low-cost way to market your research. Plus, social media allows you to have direct control over the messages you share with the world.

Although increasing and maintaining your presence effectively on social media is important, it is essential to be realistic about the amount of energy and time you might need to invest in reaching larger audiences.

These days, if you don’t have an online presence it affects which opportunities will come your way. I showed an example of someone looking for ECR conference speakers on Twitter and all suggestions in response to this were for ECRs who were on Twitter.

When someone Googles your name, what do they get? What do you want them to see? I gave my opinion on some profiles:

Google Scholar – essential. Sign up, and once you have a publication, make your profile public. Website – essential. As a minimum we add each person to the lab website with links to their professional profiles.
ORCiD – required. All lab members need an ORCiD for our publications. Easy to set up a profile and link to services that will auto-update it for you, e.g. when you publish a paper.
Twitter – important. Possibly essential these days. Many scientists are on Twitter and there are a lot of benefits to joining. It is somehow more professional than other social networks. Twitter handles can even be included on papers. Great for networking with other scientists and for following meetings. This a great guide to getting started.
LinkedIn – important outside of academia. I personally dislike LinkedIn, but it is essential if you are job-hunting outside of academic circles.
ImpactStory – not essential but fun. You can make a profile based on your ORCiD. It’s a good way to keep track of the attention that your work gets online.
Publons – might become important. This is a way to log your review activity.

Many places to set up an author profile, e.g. researcherid. Most are not worth bothering with if you have ORCiD and/or Google Scholar page.

ResearchGate – not important. It’s incredibly popular but I have never needed it and dislike it for similar reasons to LinkedIn.

How active you are on these platforms determines what you will get out of them, but as a minimum, try and keep them active and up-to-date.

I left it to the people in the lab to setup whatever accounts they like. A possibility is to get people to sign up right there in the session, but I think it’s important for everyone to make a choice about what profile(s) they want to create. The only one I require people in the lab to setup is ORCiD.

ONT assembly and Illumina polishing pipeline

Jit — Thu, 23 Nov 2017 10:13:42 -0600

This pipeline performs the following steps:

Assembly of nanopore reads using Canu.
Polish canu contigs using racon (optional).
Map a paired-end Illumina dataset onto the contigs obtained in the previous steps using BWA mem.
Perform correction of contigs using pilon and the Illumina dataset.

Address of the bookmark: https://github.com/nanoporetech/ont-assembly-polish