https://academic.oup.com/bioinformatics/article/30/18/2559/2475628
Reference-free SNP detection: dealing with the data deluge

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4083407/
GATB/DiscoSnp: DiscoSnp is designed for discovering all kinds of SNPs (not only isolated ones), as well as insertions and deletions, from raw set(s) of reads.

https://github.com/GATB/DiscoSnp
De novo assembly | Oxford Nanopore Technologies

https://nanoporetech.com/taxonomy/term/131
De novo long-read assembly of a complex animal genome | bioRxiv

https://www.biorxiv.org/content/early/2017/09/10/187054
Rapid de novo assembly of the European eel genome from nanopore sequencing reads | Scientific Reports

https://www.nature.com/articles/s41598-017-07650-6.epdf?author_access_token=dktG7e98wyRJnaEEMTcPqtRgN0jAjWel9jnR3ZoTv0P7E7t-wVGo30iojNO7dICajNY_7PE5xVPv6OoLe7hn9TeUjcZ5umREOzNoPMWkfYH58RS6uxm3vm4e4BG2AA_WKW84i6egKK271NwMq-NfzA%3D%3D
nanoporetech/ont-assembly-polish: ONT assembly and Illumina polishing pipeline

https://github.com/nanoporetech/ont-assembly-polish
Generade-nl/TULIP: TULIP - The Uncorrected Long read Itegration Pipeline

https://github.com/Generade-nl/TULIP
www.nature.com

https://www.nature.com/articles/s41598-017-03996-z
Example gallery of NanoPlot – Gigabase or gigabyte

https://gigabaseorgigabyte.wordpress.com/2017/06/01/example-gallery-of-nanoplot/
Tool documentation

https://broadinstitute.github.io/picard/command-line-overview.html
Chromosome-scale scaffolding of de novo genome assemblies based on chromatin interactions. - PubMed - NCBI

https://www.ncbi.nlm.nih.gov/pubmed/24185095
MAFFT ver.7 - a multiple sequence alignment program

https://mafft.cbrc.jp/alignment/software/algorithms/algorithms.html
Measuring the distance between multiple sequence alignments | Bioinformatics | Oxford Academic

https://academic.oup.com/bioinformatics/article/28/4/495/212883
The MUMmer 3 examples

http://mummer.sourceforge.net/examples/
MAFFT ver.7 - a multiple sequence alignment program

https://mafft.cbrc.jp/alignment/software/tips.html
Omega | Overlap-graph de novo Assembler for Metagenomics

https://omega.omicsbio.org/
abiswas-odu/Disco: Multi-threaded Distributed Memory Overlap-Layout-Consensus (OLC) Metagenome Assembler

https://github.com/abiswas-odu/Disco
SAGE: String-overlap Assembly of GEnomes | BMC Bioinformatics | Full Text

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-15-302

Fast and sensitive mapping of nanopore sequencing reads with GraphMap | Nature Communications

https://www.nature.com/articles/ncomms11307
lumpy-sv/extractSplitReads_BwaMem at master · arq5x/lumpy-sv

https://github.com/arq5x/lumpy-sv/blob/master/scripts/extractSplitReads_BwaMem
jts/nanocorrect: Experimental pipeline for correcting nanopore reads

https://github.com/jts/nanocorrect

video - how to install flash plugin on ubuntu 14.04 LTS 64-bit version - Ask Ubuntu

https://askubuntu.com/questions/469553/how-to-install-flash-plugin-on-ubuntu-14-04-lts-64-bit-version
lh3/fermi: A WGS de novo assembler based on the FMD-index for large genomes

https://github.com/lh3/fermi
Multi-metagenome

http://madsalbertsen.github.io/multi-metagenome/docs/step9.html
Bandage by rrwick

https://rrwick.github.io/Bandage/
Codon Optimization OnLine (COOL): a web-based multi-objective optimization platform for synthetic gene design | Bioinformatics | Oxford Academic

https://academic.oup.com/bioinformatics/article/30/15/2210/2391162
Genome Architecture and Evolution of a Unichromosomal Asexual Nematode - ScienceDirect

https://www.sciencedirect.com/science/article/pii/S096098221731076X?via%3Dihub#fig4
How to determine chimeras in my de novo assembly? - SEQanswers

http://seqanswers.com/forums/showthread.php?t=26721
samtools(1) manual page

http://www.htslib.org/doc/samtools.html
How To Filter Mapped Reads With Samtools

https://www.biostars.org/p/56246/
The MUMmer 3 manual

http://mummer.sourceforge.net/manual/#nucmer
assembly_olc.pdf

http://www.cs.jhu.edu/~langmea/resources/lecture_notes/assembly_olc.pdf
SAM and BAM filtering oneliners

https://gist.github.com/davfre/8596159
Inroduction to dot-plots

http://www.code10.info/index.php%3Foption%3Dcom_content%26view%3Darticle%26id%3D64:inroduction-to-dot-plots%26catid%3D52:cat_coding_algorithms_dot-plots%26Itemid%3D76
RepeatFinder Home Page

http://www.cbcb.umd.edu/software/RepeatFinder/
RepeatFinderReprint.pdf

http://www.cbcb.umd.edu/software/RepeatFinder/RepeatFinderReprint.pdf
https://bernatgel.github.io/karyoploter_tutorial//Tutorial/CreateIdeogram/CreateIdeogram.html

https://bernatgel.github.io/karyoploter_tutorial//Tutorial/CreateIdeogram/CreateIdeogram.html
Circular Visualization in R

http://zuguang.de/circlize_book/book/introduction.html#a-qiuck-glance
Creating a coverage plot using BEDTools and R

https://davetang.org/muse/2015/08/05/creating-a-coverage-plot-using-bedtools-and-r/
Eval: A software package for analysis of genome annotations | BMC Bioinformatics | Full Text

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-4-50
eval-documentation.pdf

http://mblab.wustl.edu/media/software/eval-documentation.pdf
OmicCircos: A Simple-to-Use R Package for the Circular Visualization of Multidimensional Omics Data

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3921174/
sequence - download.tardigrades.org > v1 > sequence

http://download.tardigrades.org/v1/sequence/
ksahlin/BESST: BESST - scaffolder for genomic assemblies

https://github.com/ksahlin/BESST
reubwn/scripts: Useful scripts for various things

https://github.com/reubwn/scripts
ICEberg

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Satsuma - Evolution and Genomics

http://evomics.org/learning/genomics/satsuma/
A complete bacterial genome assembled de novo using only nanopore sequencing data | Nature Methods

https://www.nature.com/articles/nmeth.3444
vezzi/FRC_align: Computes FRC from SAM/BAM file and not from afg files

https://mail.google.com/mail/u/0/#inbox
Read GTF file into R - Dave Tang's blog

https://davetang.org/muse/2017/08/04/read-gtf-file-r/

https://bernatgel.github.io/karyoploter_tutorial//Tutorial/CustomGenomes/CustomGenomes.html

https://bernatgel.github.io/karyoploter_tutorial//Tutorial/CustomGenomes/CustomGenomes.html
Dot: Interactive dot plot for genome-genome alignments

https://dnanexus.github.io/dot/
Zoho Accounts

https://accounts.zoho.eu/signin?servicename=ZohoProjects&serviceurl=https%3A%2F%2Fprojects.zoho.eu%2Fportal%2Favaga2
lh3/minimap2: A versatile pairwise aligner for genomic and spliced nucleotide sequences

https://github.com/lh3/minimap2
SSPACE-LongRead: scaffolding bacterial draft genomes using long read sequence information | BMC Bioinformatics | Full Text

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-15-211
Palindromic gene amplification — an evolutionarily conserved role for DNA inverted repeats in the genome | Nature Reviews Cancer

https://www.nature.com/articles/nrc2591
bioinformatics - BLAST DNA Sequences Reversed - Biology Stack Exchange

https://biology.stackexchange.com/questions/8160/blast-dna-sequences-reversed
LASTZ

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SOGo - (1652) Inbox

https://sogo.unamur.be/SOGo/so/jnarayan/Mail/view
Tetra-Nucleotide Analysis (TNA) | BIOiPLUG Help center

http://help.bioiplug.com/tetra-nucleotide-analysis-tna/

Clustering metagenomic contigs on tetranucleotide frequency — CGAT documentation

http://cgat.readthedocs.io/en/latest/recipes/metagenome_contigs_kmers.html

SciGenom Research Foundation (SGRF) and Institute of Genomics and Integrative Biology (IGIB) are pleased to host the Next-Generation Sequencing and Bioinformatics for Genomics & Healthcare conference.

In the ten years since the first human reference genome was completed for US$3 billion the sequencing technologies have radically changed leading to great reduction in sequencing cost. Today a human genome can be sequenced for under US$ 5000 in less than two weeks. It is expected that by the end of 2015 the cost of sequencing a human genome will drop to below thousand dollars. The next generation sequencing technologies over the past five years have enabled a large number of genomic studies that impact human health and disease. Also, this has made possible the growth of microbial, animal and plant genomics studies. While the data production has increased at a rapid pace challenges remain in analyzing and understanding the data. The conference will cover the next generation sequencing (NGS) technologies, bioinformatics for NGS and applications of NGS in many areas including personalized medicine.

For more info : http://www.scigenomconferences.com/2013/default.php

Pockets Identification

CASTp

Pocket-Finder

PocketPicker

Candidates must have: a PhD degree in statistics, biostatistics or bioinformatics, extensive experience in analyzing high-dimensional data (microarray, SNP, CNVs) and of validation approaches. In addition, experience in penalized regression methods, data base manipulation; and strong programming skills in order to conduct Monte Carlo studies and applications (R). Candidate must have excellent communication skills (verbal, written and presentation), a strong proficiency in Linux system.

This position is available immediately and will be filled as soon as possible. Appointment could be extended beyond the first year based on additional funding.

For more information about the Department of Biostatistics and Bioinformatics, please visit our website: http://www.biostat.duke.edu.

For more info: http://biostat.duke.edu/sites/biostat.duke.edu/files/Halabi%20-%20Postdoc%20Job%20Posting%202013%20updated.pdf

Duke University is an Equal Opportunity/Affirmative Action Employer.

Many times in bioinformatics we need to deal with huge datasets which  are more than 100GB size. The traditional way to analysis a file is using the while loop

while (FILE){

Do something;

}

This is very slow(since we are using only one processor) and if we have 500 million lines in the dataset it takes more than a day to iterate through the whole dataset. So how do we make best use of all our processors and get the work done quickly?

Here is a very simple and efficient technique with perl which i have been using. I am  more inclined towards using perl fork than perl threads.

One of the oldest way to fork is

my $fork = fork();
if($fork){   
push (@childs,$fork); 
}
elseif($fork==0){
your code here;
exit(0);
}
else{die “Couldnt fork : $!”;}

## wait for the child process to finish
foreach(@childs){
my $tmp=waitid($_,0);
}

what a fork does is it creates a child process and takes the variables and code with it to analyze it separately (detached from the parent process) and thus a separate process is created( which usually runs on a separate processor). Thats it!! One big disadvantage of forking is its very difficult to share variables among the different processes. I will show you how to do it easily but still it has its own drawbacks.

Okie, now if you really do not want to use fork in your code, that’s okie too..There are many useful modules which do it for you very efficiently. One really useful module is Parallel::ForkManager. You can use Parallel::ForkManager to manage the number of forks you want to generate (number of processors you want to use).

Simple usage:
use Parallel::ForkManager;
my $max_processors=8;
my $fork= new Parallel::ForkManager($max_processors);
foreach (@dna) {
$fork->start and next; # do the fork
you code here;
$fork->finish; # do the exit in the child process
}
$pm->wait_all_children;

so you will be generating 8 forks which do the same thing for your each element of array. when one child finishes, Parallel::ForkManager generates a new one and thus you will be using all your processors to analyze the data. Now, if you have generated 8 child processes and want to write the data to one file. You need to lock the file to do this, because you will have problems with the buffering. You can lock the file using flock command.

open (my $QUAL, “myfile.txt”);
flock $QUAL, LOCK_EX or die “cant lock file $!”;
print $QUAL “$output”;
flock $QUAL, LOCK_UN or die “$!”;
close $QUAL;

I would not suggest using flock when dealing with multiple processes because it will decrease the processing efficiency( each child process must wait for the lock to be released by the other child process). Instead, I would suggest each fork writing to a separate file and after the processing just concatenating them.

Putting it all together, If you have 100GB data you can do this

step 1 : split the dataset equally according to number of processors you have. this may take a few hours(about 2-3 hrs for 100GB file)
You can use unix “split” command for this
for example:
my $number_split=int($number_of_entries_in_your_dataset/$max_processors);
my $split_Files=`split -l $number_split “your_file.fasta” “file_name”`;

step2: open you directory comtaining you split files and start Parallel::ForkManager.
For example:
opendir(DIRECTORY, $split_files_directory) or die $!; ### open the directory
my $fork= new Parallel::ForkManager($max_processors);
while (my $file = readdir(DIRECTORY)) { ### read the directory
if($file=~/^\./){next;}
print $file,”\n”;
########## Start fork ##########
my $pid= $super_fork->start and next;
Whatever you want to do with the split file ;
analyze my piece of $file;
######### end fork ###############
$super_fork->finish;
}
$super_fork->wait_all_children;

So basically each processor will be active with its piece of data (split file) and thus you have created 8 processes at one time which run without interfering with the other process. I again will not suggest writing output from each child process to one file(for reasons above). Write output from each fork to a separate file and finally concatenate them. Thats it, you have just increased your program speed by 8 times!! Isnt it easy?

Note:
You may worry about concatenation of the output each child generates, since it does take some time(remember 100GB). I think now you can use a mysql database LOAD DATA LOCAL INFILE command to load all the files into a single table(Should take about 3hrs for 100Gb dataset) and then export the whole table into one file. This should be faster than just concatenating them using “cat” command.(correct me if I am wrong)

Or much simpler way is to use pipes

cat output_dir/* | my_pipe or my_pipe <(file1) final_file;

Thats it guys!! Enjoy programming and please do comment. I am not a computer scientist so forgive me for any mistakes and if any please report them. Thank you.

Requirements
- 3-5 years of relevant bioinformatics experience such as public data mining,
processing, analysing and visualising omics data, etc.
- Ph.D., Masters or Bachelors in Bioinformatics, Biotechnology,
Computational Biology, or related field.
- Understanding of molecular biology and biochemistry.
- Comfort and experience with biological research and data.
- Proficient in a programming language used for bioinformatics such as R or
python.
- Excellent communication skills.
- Ability to summarise and simplify complex analyses for a non-technical
audience.
- Strong analytical skills, curiosity and a knack to solve difficult problems.
- Work well in multi-disciplinary teams with people of vastly different
backgrounds.
- Demonstrated success in collaboration and independent work.

More at https://angel.co/elucidata/jobs/460104-senior-bioinformatics-scientist

Candidate:
The candidate is expected to have B.S. or M.S. degree in the disciplines such as Computer Science, Statistics, Applied Mathematics, Physics or Electrical Engineering. The candidates with the backgrounds in Life Science disciplines such as Bioinformatics, Computational or Quantitative Biology will also be considered.

Location:
The position is available at LAPTI (http://lapti.ucc.ie) that is located in the Western Gate Building (http://www.stwarchitects.com/project-information.php?c=1&p=09993) at University College Cork. Western Gate Building Research Complex hosts several UCC departments and provides ideal environment for interdisciplinary research. Cork (sometimes referenced as “Venice of Ireland”) is the second most populous city in the Republic. It has friendly cosmopolitan atmosphere and vibrant culture. A number of American industrial giants such as Apple , EMC and Pfizer have chosen Cork as a home for their European headquarters.

Application process:
The details of the application process are given at http://lapti.ucc.ie/jobs.html. To ensure prompt processing of your application use the subject line: ‘Ph.D. computational’. All applications received prior to August the 1st are guaranteed equal consideration. However, applications at the later dates will also be considered until the position is filled.

Interested applicants must submit CV and addresses of three references to ataulfo@unam.mx.

Tenure Track position in Genomic Sciences

Laboratorio Internacional de Investigación sobre el Genoma Humano, UNAM Juriquilla, Querétaro, México

The International Laboratory for Human Genome Research, LIIGH-UNAM (www.liigh.unam.mx) offers a tenure-track position at the level of Assistant Professor (Investigador Asociado C) to perform research, teaching and formation of human resources in the area of: “Genomics of Mendelian Diseases”

Applicants are expected to have a doctorate degree, postdoctoral experience related to the above mentioned area and a strong track record of peer-reviewed publications. Interested applicants must submit CV, email addresses of three references, and a three-page project to Dr. Rafael Palacios, Coordinator of LIIGH-UNAM (palacios@liigh.unam.mx) before June 21, 2019 ………………………………………………………………

Tenure Track position in Genomic Sciences

Laboratorio Internacional de Investigación sobre el Genoma Humano, UNAM Juriquilla, Querétaro, México

The International Laboratory for Human Genome Research, LIIGH-UNAM (www.liigh.unam.mx) offers a tenure-track position at the level of Assistant Professor (Investigador Asociado C) to perform research, teaching and formation of human resources in the area of: “Statistic Population Genomics and its Impact in Complex Diseases”

Applicants are expected to have a doctorate degree, postdoctoral experience related to the above mentioned area and a strong track record of peer-reviewed publications. Interested applicants must submit CV, email addresses of three references, and a three-page statement of research interests to Dr. Rafael Palacios, Coordinator of LIIGH-UNAM (palacios@liigh.unam.mx) before June 21, 2019

Dated : 04 Dec 2013 - 06 Dec 2013

More at : http://www.clinicalgenomicsinformatics.com/