The manual translation of many, frequently rather complex SPSS scripts often presents itself as a tedious and error-prone task, and represents a rather large obstacle for many analysts and companies to migrate to a modern, open source data management and analysis tool like R. With translate2R this hurdle will be diminished substantially.

Find at https://service.eoda.de/translater/?lang=en

Pine Biotech, Inc., a US-based startup working with the Tauber Bioinformatics Research Center is offering a full curriculum online preparing students without any technical background for real-life challenges with large scale biomedical data. Workshops on processing, analysis and biomedical interpretation of Next Generation Sequencing data cover important up-to-date algorithms and machine learning approaches. The most important thing is that there are virtually no pre-requisites such as coding, biostatistics or advanced medical skills. If you know what gene is and how the genes are expressed, you are ready to take the courses or join our workshops. Learn more: https://edu.t-bio.info/workshops/

Install latest Perl (with supporting multithreading) and CPANMinus.

 $ cd
 $ git clone git://github.com/tokuhirom/plenv.git ~/.plenv
 $ git clone git://github.com/tokuhirom/Perl-Build.git ~/.plenv/plugins/perl-build/
 $ echo 'export PATH="$HOME/.plenv/bin:$PATH"' >> ~/.bashrc
 $ echo 'eval "$(plenv init -)"' >> ~/.bashrc
 $ source ~/.bashrc
 $ plenv install 5.18.1 -Dusethreads
 $ plenv rehash
 $ plenv global 5.18.1
 $ plenv install-cpanm

• git is a distributed revision control and source code management software which can help you to download files from GitHub server.
• echo means "print".
• >> means adding the output into the end of the file, while > means adding the output by overwriting the whole file. Please use> with additional cares.
• In Linux system, there are two types of outputs when you execute a command. One is called standard output (or sometimes STDOUT for short), and the other is a standard error (STDERR). 1> is for STDOUT only, 2> is for STDERR only, and &>means for both. In default > is the same to 1>.
• exec is execution.
• Remember to install Perl in supporting multithreading (with option -Dusethreads), which is important for many NGS analysis packages (e.g. Trinity). In this setting, you can use multiple CPU for Perl software.
• Install the CPAN (Comprehensive Perl Archive Network) manager software, CPANMinus, by install-cpanm.

You can use plenv global and plenv local to change the different version of Perl to fulfil different needs of your Perl software.

For example, if the specific version of Perl is not compatible with your script, you can switch to the different version by:

 $ plenv local 

• It is similar to set the local version of your script language when you use pyenv and rbenv as the following.

Put the following path into ~/.bashrc file.

export PERL5LIB="$HOME/.plenv/build/perl-5.18.1/lib"

Install BioPerl and PerlIO::gzip

CPANMinus is a very good Perl module manager, use cpanm to install BioPerl can save you a lot of time. Here are some useful modules:

$ cpanm Bio::Perl
$ cpanm Bio::SearchIO
$ cpanm PerlIO::gzip

For more information, please visit: https://github.com/tokuhirom/plenv

Additional Information:

If you have any questions about scientific aspects of this position, please contact Prof. Lars Bertram, head of LIGA (lars.bertram@uni-luebeck.de).

Please contact Ms. Anna Wolbert for further questions about administrative details (recruiting@uksh.de).

Weitere Informationen erhalten Sie auch unter www.uksh.de/karriere.

Wir freuen uns auf Ihre Bewerbung bis zum 15.03.2020 unter Angabe unserer Ausschreibungsnummer 20190570.119.CL.

• -e Makes the line of code be executed instead of a script
• -n Forces your line to be called in a loop. Allows you to take lines from the diamond operator (or stdin)
• -p Forces your line to be called in a loop. Prints $_ at the end

• This counts the number of quotation marks in each line and prints it

  perl -ne '$cnt = tr/"//;print "$cnt\n"' inputFileName.txt

• Adds string to each line, followed by tab

  perl -pe 's/(.*)/string\t$1/' inFile > outFile

• Append a new line to each line

  perl -pe 's//\n/' all.sent.classOnly > all.sent.classOnly.sep

• Replace all occurrences of pattern1 (e.g. [0-9]) with pattern2

  perl -p -i.bak -w -e 's/pattern1/pattern2/g' inputFile

• Go through file and only print words that do not have any uppercase letters.

  perl -ne 'print unless m/[A-Z]/' allWords.txt > allWordsOnlyLowercase.txt

• Go through file, split line at each space and print words one per line.

  perl -ne 'print join("\n", split(/ /,$_));print("\n")' someText.txt > wordsPerLine.txt

• or in other words, delete every character that is not a letter, white space or line end (replace with nothing)

  perl -pne 's/[^a-zA-Z\s]*//g' text_withSpecial.txt > text_lettersOnly.txt

• perl -pne 'tr/[A-Z]/[a-z]/' textWithUpperCase.txt > textwithoutuppercase.txt;

• Print only the second column of the data when using tabular as a separator

  perl -ne '@F = split("\t", $_); print "$F[1]";' columnFileWithTabs.txt > justSecondColumn.txt

• One-Liner: Sort lines by their length

  perl -e 'print sort {length $a <=> length $b} <>' textFile

• One-Liner: Print second column, unless it contains a number

  perl">perl -lane 'print $F[1] unless $F[1] =~ m/[0-9]/' wordCounts.txt

Prokka – Standalone command line tool, takes just a few minutes per genome. This is the best way to get good quality annotation in a flash, which is particularly useful if you have loads of genomes or need to annotate a pangenome or metagenome. Note however that the quality of functional information is not as good as RAST, and you will need several extra steps if you want to do functional profiling and pathway analysis of your genome(s)… which is in-built in RAST.

NCBI Prokaryotic Genome Annotation Pipeline is designed to annotate bacterial and archaeal genomes (chromosomes and plasmids).

Genome annotation is a multi-level process that includes prediction of protein-coding genes, as well as other functional genome units such as structural RNAs, tRNAs, small RNAs, pseudogenes, control regions, direct and inverted repeats, insertion sequences, transposons and other mobile elements.

PGAP: NCBI has developed an automatic prokaryotic genome annotation pipeline that combines ab initio gene prediction algorithms with homology based methods. The first version of NCBI Prokaryotic Genome Automatic Annotation Pipeline (PGAAP; see Pubmed Article) developed in 2005 has been replaced with an upgraded version that is capable of processing a larger data volume.  NCBI's annotation pipeline depends on several internal databases and is not currently available for download or use outside of the NCBI environment.

BEACON (automated tool for Bacterial GEnome Annotation ComparisON), a fast tool for an automated and a systematic comparison of different annotations of single genomes. The extended annotation assigns putative functions to many genes with unknown functions. BEACON is available under GNU General Public License version 3.0 and is accessible at: http://www.cbrc.kaust.edu.sa/BEACON/.

BlastKOLA: Assigns K numbers to the user's sequence data by BLAST searches, respectively, against a nonredundant set of KEGG GENES. KOALA (KEGG Orthology And Links Annotation) is KEGG's internal annotation tool for K number assignment of KEGG GENES using SSEARCH computation. Annotate Sequence in KEGG Mapper and Pathogen Checker in KEGG Pathogen are special interfaces to this server and can be executed in an interactive mode. BlastKOALA is suitable for annotating fully sequenced genomes.

PAGIT: Provides a toolkit for improving the quality of genome assemblies created via an assembly software. PAGIT compiled four tools: (i) ABACAS which classifies and orientates contigs and estimates the sizes of gaps between them; (ii) IMAGE uses paired-end reads to extend contigs and close gaps within the scaffolds; (iii) ICORN for identifying and correcting small errors in consensus sequences and; (iv) RATT for help annotation. The software was mainly created to analyze parasite genomes of up to about 300 Mb.

MAKER: A portable and easily configurable genome annotation pipeline. MAKER allows smaller eukaryotic and prokaryotic genome projects to independently annotate their genomes and to create genome databases. It identifies repeats, aligns ESTs and proteins to a genome, produces ab-initio gene predictions and automatically synthesizes these data into gene annotations having evidence-based quality values. MAKER's inputs are minimal and its ouputs can be directly loaded into a Generic Model Organism Database (GMOD). They can also be viewed in the Apollo genome browser; this feature of MAKER provides an easy means to annotate, view and edit individual contigs and BACs without the overhead of a database. MAKER is available for download and can be tested online via the MAKER Web Annotation Service (MWAS).

MyPro is a software pipeline for high-quality prokaryotic genome assembly and annotation. It was validated on 18 oral streptococcal strains to produce submission-ready, annotated draft genomes. MyPro installed as a virtual machine and supported by updated databases will enable biologists to perform quality prokaryotic genome assembly and annotation with ease.

Following are the list of tools commonly used to PPIs predictions:

Protein-Protein Interaction Sites

PPISP

A consensus neural network method for predicting protein-protein interaction sites

HOMCOS

A server to predict interacting protein pairs and interacting sites by homology modeling of complex structures

HotPOINT

Prediction of protein interfaces using an empirical model

ISIS

Prediction of interaction hotspots from sequence

KFC server

Automated decision-tree approach to predicting protein-protein interaction hot spots

meta-PPISP

A meta server for predicting protein-protein interaction sites. meta-PPISP is built on three individual web servers: cons-PPISP, PINUP, and Promate

ODA

Identification of optimal surface patches with the lowest docking desolvation energy values

PINUP

Protein binding site prediction with an empirical scoring function

Other Sites (DNA, RNA, Metals)

CHED 

Web server for predicting soft metal binding sites in proteins

DBD-Hunter

A knowledge-based method for the prediction of DNA-protein interactions

DISPLAR

Given the structure of a protein known to bind DNA, the method predicts residues that contact DNA using neural network method

iDBPs

Predicts DNA binding proteins for proteins with known 3D structure.

PFplus

Below you can find a few basic tutorials for how to run MITObim and I encorage you to give them a try with the testdata that comes with this Repo, just to make sure everything is running smoothly on your system. It'll only take a few minutes and will potentially safe you a lot of time down the line.

I provide further examples here as Jupyter notebooks. Get in touch if you feel like sharing your particular MITObim solution and I'd be happy to put it up here, too!

Address of the bookmark: https://github.com/chrishah/MITObim

https://www.nature.com/articles/nmeth.4432

Address of the bookmark: https://github.com/xiaochuanle/MECAT