BOL: Related items

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...

Porechop: tool for finding and removing adapters from Oxford Nanopore reads

Rahul Nayak — Tue, 29 May 2018 07:33:44 -0500

Porechop is a tool for finding and removing adapters from Oxford Nanopore reads. Adapters on the ends of reads are trimmed off, and when a read has an adapter in its middle, it is treated as chimeric and chopped into separate reads. Porechop performs thorough alignments to effectively find adapters, even at low sequence identity.

Porechop also supports demultiplexing of Nanopore reads that were barcoded with the Native Barcoding Kit, PCR Barcoding Kit or Rapid Barcoding Kit.

Address of the bookmark: https://github.com/rrwick/Porechop

RNA-seq Analysis Workshop Course Materials

Jit — Tue, 03 Jul 2018 08:14:14 -0500

RNAseq can be roughly divided into two "types": Reference genome-based - an assembled genome exists for a species for which an RNAseq experiment is performed. It allows reads to be aligned against the reference genome and significantly improves our ability to reconstruct transcripts. This category would obviously include humans and most model organisms but excludes the majority of truly biologically intereting species (e.g., Hyacinth macaw); Reference genome-free - no genome assembly for the species of interest is available. In this case one would need to assemble the reads into transcripts using de novo approaches. This type of RNAseq is as much of an art as well as science because assembly is heavily parameter-dependent and difficult to do well. In this lesson we will focus on the Reference genome-based type of RNA seq. http://chagall.med.cornell.edu/RNASEQcourse/

Address of the bookmark: http://chagall.med.cornell.edu/RNASEQcourse/

Assistant Professor in Bioinformatics at Dr. D. Y. Patil Biotechnology & Bioinformatics Institute

Tue, 03 Jun 2014 19:54:15 -0500

Dr. D. Y. Patil Biotechnology & Bioinformatics Institute
Tathawade, Pune 411033.

Assistant Professor in Bioinformatics

Essential :
First Class Master’s Degree in the appropriate branch of Life Sciences / Technology (Tech.)
OR
Ph.D in Life Sciences or in the respective subject area of specialization
OR
Good Academic record with at least 55% marks (or an equivalent grade) at the Master’s Degree level, in the relevant subject or an equivalent degree from an Indian / Foreign University.
Besides fulfilling the above qualifications, candidates should have cleared the eligibility test (NET) for lecturers conducted by the UGC, CSIR or similar test accredited by the UGC and as per the requirements of UGC guidelines.

Desirable :
Teaching, research industrial and/or professional experience in a reputed organization.
Papers presented at Conferences and/or in refereed journals

Note : Application are invited in prescribed form Click here for Application Form
Kindly send your applications to “Registrar, Dr. D. Y. Patil Vidyapeeth, Pune, Sant Tukaram Nagar, Pimpri, Pune – 411018., Maharashtra, India.” should reach in the University office within 15 days from the publication.

More Info: http://www.dpu.edu.in/BiotechResearchPositions.aspx

Convert EnsEMBL GTF to Annotation table (Geneid, GeneSymbol, GeneWiseChrLocation, GeneClass, Strand) Raw

EagleEye — Fri, 24 Jun 2016 18:08:49 -0500

Bash Script source:

https://gist.github.com/santhilalsubhash/367befcf5216be4b1fd9

Information:

This script converts EnsEMBL GTF (Ex: https://gist.githubusercontent.com/santhilalsubhash/1e7cca357e52a181dc25/raw/cfb803e07900a2baefbb6534f1299fd30cb57a29/sample.GTF) file to annotation table format. It generated two files
1) Transcript wise chromosome location with information about transcripts (Ex: https://gist.githubusercontent.com/santhilalsubhash/c7dec516e0338503a4b6/raw/de0af1a39f0005c4ce7321c5ae57fc8b4a14c7f4/sample.GTF_enst_annotation.txt)
2) Gene wise chromosome location with information about genes (Ex: https://gist.githubusercontent.com/santhilalsubhash/c92006c5080f0333bec2/raw/d16e0b2440d73b09b486d3c9751cdb248a73fa0b/sample.GTF_ensg_annotation.txt)

Note: You can download GTF files from http://www.ensembl.org/info/data/ftp/index.html

Faculty post at Zhejiang University

Tue, 10 Jun 2014 03:40:40 -0500

Zhejiang University (ZJU) is seeking faculty candidates for its newly launched, highly competitive and well funded “Hundred Talents Program”. This search covers all colleges and departments at ZJU. Applicants, expected to be about 35 years old, should hold PhD degree, and postdoctoral experiences are preferred for applicants in most fields. Applicants should have demonstrated commitment to excellence in teaching and research at a level comparable to the academic achievement of assistant professor or associate professor in world-renowned universities. Successful candidates must work full-time and are expected to establish internationally competitive and independent research program in cutting-edge areas of the relevant field at ZJU.

As one of the leading research-intensive universities in China, ZJU is located in the beautiful city of Hangzhou. Successful candidates will be employed as Principal Investigators and are qualified to supervise doctoral students. ZJU will offer an internationally competitive salary and the opportunity to purchase university's apartment at a price much lower than the market price, and will provide office and laboratory spaces as well as internationally competitive research startup packages.

Qualified applicants are strongly encouraged to submit their applications electronically to tr@zju.edu.cn. Applicants should include the following materials in pdf format: a comprehensive CV, a statement of research and teaching plan, and a list of 3 to 5 references with detailed contact information.

Contact：Talents Office, ZJU

Tel：+86-571-88981345, +86-571-88981390

Fax：+86-571-88981976

E-mail:tr@zju.edu.cn

ComparativeGenomics Exercise2

Neel — Wed, 22 Aug 2018 22:10:56 -0500

COMPARATIVE MICROBIAL GENOMICS ANALYSIS WORKSHOP @ cbs.dtu.dk

Free Bioinformatics workbench https://www.mn.uio.no/ifi/english/research/networks/clsi/earlier_seminars/2012/tammivesth_osloseminarfinal.pdf

XAMPP: Starting Apache fail Ubuntu

Ram Yash Pal — Sat, 07 Jun 2014 05:52:35 -0500

Once you install XAMMP on linux, the most common problem you face is Apache failure. To fix the issues please use following command to first stop and then again start it.

sudo /etc/init.d/apache2 stop

sudo /etc/init.d/mysql stop

sudo /etc/init.d/proftpd stop

sudo /opt/lampp/lampp start

PhpMyAdmin “Wrong permissions on configuration file, should not be world writable!”

Once the Xammp is installed, it might be possible to set up the configuration file in writable mode. Try the following steps:

Just chmod 0755 the file

sudo chmod 0755 config.inc.php

BASE: a practical de novo assembler for large genomes using long NGS reads

Rahul Nayak — Fri, 19 Oct 2018 07:25:21 -0500

new de novo assembler called BASE. It enhances the classic seed-extension approach by indexing the reads efficiently to generate adaptive seeds that have high probability to appear uniquely in the genome. Such seeds form the basis for BASE to build extension trees and then to use reverse validation to remove the branches based on read coverage and paired-end information, resulting in high-quality consensus sequences of reads sharing the seeds. Such consensus sequences are then extended to contigs.

Address of the bookmark: https://github.com/dhlbh/BASE

CANU genome assembly parameters !

Rahul Nayak — Mon, 07 Jan 2019 08:40:37 -0600

Choose the appropriate parameters to run Canu and run it. The assembly will take about an hour. You can use two cores (parameter -maxThreads=2) and you would like to disable cluster option, since we compute on a single Amazon server set off the option to compute on cluster useGrid=false. This specifications should be for your project discussed with a local computing guru. The parameters that are in square brackets [] are optional, symbol | stands for "or".

usage:   canu [-correct | -trim | -assemble | -trim-assemble] \
              [-s ] \
               -p  \
               -d  \
               genomeSize=[g|m|k] \
               -maxThreads=2 \
               useGrid=false \
              [other-options] \
               read_file.fastq.gz

A default Canu run produces usually high quality assembly, example of a command that was used for testing can be found below. However, there are still a lot of parameters that are possible to tweak. For example if we desire to assemble haplotypes separately of if we want to smash them together, we can alternate the error correction process.

canu -p test_asmbl \
     -d asm_test3 \
     genomeSize=2m \
     -maxThreads=2 useGrid=false \
     -pacbio-raw \ ~/pacbio/dna/sample_reads.fastq.gz

There is a brilliant section in documentation about parameter tweaking.

The output directory contains will contain many files. The most interesting ones are:

*.correctedReads.fasta.gz : file containing the input sequences after correction, trim and split based on consensus evidence.
*.trimmedReads.fastq : file containing the sequences after correction and final trimming
*.layout : file containing informations about read inclusion in the final assembly
*.gfa : file containing the assembly graph by Canu
*.contigs.fasta : file containing everything that could be assembled and is part of the primary assembly

The basic stats of assembly can be read from reports generated by the assembler, or calculated using standard UNIX command line tools.

More at https://canu.readthedocs.io/en/latest/faq.html