BOL: Related items

Bioinformatician stuck in wet-lab

Rahul Agarwal — Tue, 06 May 2014 12:46:56 -0500

This guide is aimed at pet bioinformaticians, and is meant to guide them towards better career development.

1. Make friends with local bioinformatics groups
2. Talk to your computing group
3. Obtain clear expectations
4. Rewrite your job description
5. Papers
6. Attend bioinformatics meetings
7. Try first, ask later

Address of the bookmark: http://biomickwatson.wordpress.com/2013/04/23/a-guide-for-the-lonely-bioinformatician/

MIX: Combining multiple assemblies from NGS data

Rahul Nayak — Tue, 08 May 2018 04:58:05 -0500

Mix is a tool that combines two or more draft assemblies, without relying on a reference genome and has the goal to reduce contig fragmentation and thus speed-up genome finishing. The proposed algorithm builds an extension graph where vertices represent extremities of contigs and edges represent existing alignments between these extremities. These alignment edges are used for contig extension. The resulting output assembly corresponds to a path in the extension graph that maximizes the cumulative contig length.

The Mix algorithm, approach and results were published in BMC bioinformatics : http://www.biomedcentral.com/1471-2105/14/S15/S16.

Address of the bookmark: https://github.com/cbib/MIX

Science for Life Laboratory (SciLifeLab)-Sweden

Sat, 10 May 2014 06:22:30 -0500

Science for Life Laboratory (SciLifeLab) is a national center for molecular biosciences with focus on health and environmental research. The center combines frontline technical expertise with advanced knowledge of translational medicine and molecular bioscience. SciLifeLab is a national resource and a collaboration between four universities: Karolinska Institutet, KTH Royal Institute of Technology, Stockholm University and Uppsala University.

Webpage : https://www.scilifelab.se/about-us/
Opportunity: https://www.scilifelab.se/about-us/career/

HALC: High throughput algorithm for long read error correction

Jit — Fri, 08 Jun 2018 10:47:41 -0500

HALC, a high throughput algorithm for long read error correction. HALC aligns the long reads to short read contigs from the same species with a relatively low identity requirement so that a long read region can be aligned to at least one contig region, including its true genome region’s repeats in the contigs sufficiently similar to it (similar repeat based alignment approach) HALC was able to obtain 6.7-41.1% higher throughput than the existing algorithms while maintaining comparable accuracy. The HALC corrected long reads can thus result in 11.4-60.7% longer assembled contigs than the existing algorithms.

Address of the bookmark: https://github.com/lanl001/halc

KAT: a K-mer analysis toolkit to quality control NGS datasets and genome assemblies

Jit — Fri, 06 Jul 2018 03:36:45 -0500

KAT is a suite of tools that analyse jellyfish hashes or sequence files (fasta or fastq) using kmer counts. The following tools are currently available in KAT:

hist: Create an histogram of k-mer occurrences from a sequence file. Adds metadata in output for easy plotting.
gcp: K-mer GC Processor. Creates a matrix of the number of K-mers found given a GC count and a K-mer count.
comp: K-mer comparison tool. Creates a matrix of shared K-mers between two (or three) sequence files or hashes.
sect: SEquence Coverage estimator Tool. Estimates the coverage of each sequence in a file using K-mers from another sequence file.
blob: Given, reads and an assembly, calculates both the read and assembly K-mer coverage along with GC% for each sequence in the assembly.SEquence Coverage estimator Tool.
filter: Filtering tools. Contains tools for filtering k-mer hashes and FastQ/A files:
- kmer: Produces a k-mer hash containing only k-mers within specified coverage and GC tolerances.
- seq: Filters a sequence file based on whether or not the sequences contain k-mers within a provided hash.
plot: Plotting tools. Contains several plotting tools to visualise K-mer and compare distributions. The following plot tools are available:
- density: Creates a density plot from a matrix created with the "comp" tool. Typically this is used to compare two K-mer hashes produced by different NGS reads.
- profile: Creates a K-mer coverage plot for a single sequence. Takes in fasta coverage output coverage from the "sect" tool
- spectra-cn: Creates a stacked histogram using a matrix created with the "comp" tool. Typically this is used to compare a jellyfish hash produced from a read set to a jellyfish hash produced from an assembly. The plot shows the amount of distinct K-mers absent, as well as the copy number variation present within the assembly.
- spectra-hist: Creates a K-mer spectra plot for a set of K-mer histograms produced either by jellyfish-histo or kat-histo.
- spectra-mx: Creates a K-mer spectra plot for a set of K-mer histograms that are derived from selected rows or columns in a matrix produced by the "comp".

In addition, KAT contains a python script for analysing the mathematical distributions present in the K-mer spectra in order to determine how much content is present in each peak.

This README only contains some brief details of how to install and use KAT. For more extensive documentation please visit: https://kat.readthedocs.org/en/latest/

https://academic.oup.com/bioinformatics/article/33/4/574/2664339

Address of the bookmark: https://github.com/TGAC/KAT

Professor/Associate Professor/ Assistant Professor at Chettinad Academy of Research and Education

Sat, 24 May 2014 00:00:15 -0500

OPEN FACULTY POSITION

Chettinad Academy of Research and Education (CARE) invites applications from eligible and translational research-oriented candidates to the posts of Professor/Associate Professor/ Assistant Professor Computational Biology, Bioinformatics, and Pharmaceutical Chemistry.

Emoluments: As per UGC norms (Adequate Compensation for Postdoctoral/Teaching experience)

Candidates fulfilling the eligibility criteria as per the UGC norms can send their full CV with copies of certificates and reference letters to the following address by post or by e-mail on or before 31st May 2014

The Registrar,
Chettinad Academy of Research and Education,
Chettinad Health City
Kelambakkam, Chennai 603 103
Tamil Nadu
T +91 (0)44 4741 1000
F +91 (0)44 4741 1011
Email: jobs @chettinadhealthcity.com

Advertisement: http://182.73.176.163/chc/ads2014.pdf

The Minerva Research Group for Bioinformatics

Tue, 27 May 2014 15:48:14 -0500

The focus of the bioinformatics group is to use computational approaches to gain an insight into genome evolution in primates.

http://www.eva.mpg.de/genetics/bioinformatics/overview.html?Fsize=0%2C%20%40%2F%27

Kelso Group
Department of Evolutionary Genetics
Max Planck Institute for Evolutionary Anthropology
Deutscher Platz 6
04103 Leipzig
Germany
Phone: +49 341 3550 500

Job:
http://www.eva.mpg.de/genetics/bioinformatics/jobs.html?Fsize=0%2C%2B%40

nQuire: a statistical framework for ploidy estimation using next generation sequencing

Jit — Thu, 04 Oct 2018 05:23:59 -0500

nQuire provides a statistical framework to study organisms with intraspecific variation in ploidy. nQuire is likely to be useful in epidemiological studies of pathogens, artificial selection experiments, and for historical or ancient samples where intact nuclei are not preserved. It is implemented as a stand-alone Linux command line tool in the C programming language and is available at https://github.com/clwgg/nQuireunder the MIT license.

Address of the bookmark: https://github.com/clwgg/nQuireunder

Monitor running jobs on Linux server

Jitendra Narayan — Fri, 06 Jun 2014 16:18:43 -0500

You as a bioinformatican run lots of program on your servers. Sometime the shared server is also used by your colleague. If server is busy you sometime need to check the running programs and want to monitor the running programs as well. The "top" command will come in handy when you need to find out if things are still running, how long they’ve been running, or how much memory is being used.

‘top’ is very simple to run: type

%% top

You’ll get a screen that looks like this, and is updated regularly:

Simple, right? Heh.

First! Note that you can use ‘q’ or ‘CTRL-C’ to exit from ‘top’.

Now let’s read and understand at each line independently.

The first line:

top - 23:00:48 up 39 days, 2 user, load average: 0.00, 0.00, 0.00

The first line tells you the current time, how long the machine has been up, how many users are logged in, and the short/medium/long-term compute load on the machine. If you run something for a long time, you’ll see these numbers go up. Right now, the machine is basically just sitting there, so these are all close to 0.

The second line:

Tasks: 239 total,   1 running, 238 sleeping,   0 stopped,   0 zombie

This line tells you how many processes are running. If you are using laptops machines it’s not so interesting because you really are the only one using this machine.

Cpu(s): 0.0%us, 0.0%sy, 0.0%ni,100.0%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st

This line contains the CPU load. The first two numbers are how busy the system is doing computation (“us” stands for “user”) and how busy the system is doing system-y things like accessing disks or network (“sy” stands for “system”). We’ll talk more about this later.

Mem:   49457320k total,    3492174k used, 14535596k free,    1435148k buffers

This should be easy to understand – how much memory you’re using!

Swap:   539356k total,   28332k used,   836562k free,    29862014k cached

Swap is just on-disk memory that can be used to “swap” out programs from main memory. Again, we’ll talk about this later.:

PID USER      PR NI VIRT RES SHR S %CPU %MEM    TIME+ COMMAND
1 root      39 19 0 0 0 S 0.0 0.0   246:57.22 kipmi0
2 root      RT   0     0    0    0 S 0.0 0.0   0:00.00 migration/0

And... finally! What’s actually running! The two most important numbers are the %CPU and %MEM towards the right, as well as the COMMAND. This tells you how compute- and memory-intensive your program is. Right now, nothing’s running so the numbers aren’t very interesting, but just wait until we run something...

AMStat: display statistics of large sequence files from next generation sequencing projects

Neel — Fri, 09 Nov 2018 13:34:56 -0600

SAMStat is an efficient C program to quickly display statistics of large sequence files from next generation sequencing projects. When applied to SAM/BAM files all statistics are reported for unmapped, poorly and accurately mapped reads separately. This allows for identification of a variety of problems, such as remaining linker and adaptor sequences, causing poor mapping. Apart from this SAMStat can be used to verify individual processing steps in large analysis pipelines.

Address of the bookmark: http://samstat.sourceforge.net/