We have developed panHiTE, a comprehensive and accurate pipeline for TE detection in large-scale population genomes. It has been successfully applied to hundreds of plant population genomes, demonstrating its effectiveness and scalability.

For detailed instructions, please refer to the panHiTE tutorial.

Address of the bookmark: https://github.com/CSU-KangHu/HiTE

2. Parallel sequencing lives, or what makes large sequencing projects successful https://academic.oup.com/gigascience/article/6/11/gix100/4557140?login=false

3. Common-sense approaches to sharing tabular data alongside publication https://www.sciencedirect.com/science/article/pii/S2666389921002300

4. A Reproducible Data Analysis Workflow with R Markdown, Git, Make, and Docker https://psyarxiv.com/8xzqy/

5. Practical Computational Reproducibility in the Life Sciences https://www.cell.com/cell-systems/fulltext/S2405-4712(18)30140-6

6. A video by Dr.Keith A. Baggerly from MD Anderson [The Importance of Reproducible Research in High-Throughput Biology](https://www.youtube.com/watch?v=7gYIs7uYbMo) highly recommended.

7. Ten Simple Rules for Reproducible Computational Research http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003285)

8. Good Enough Practices in Scientific Computing http://arxiv.org/abs/1609.00037 

9. Best Practices for Scientific Computing https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001745

10. A Quick Guide to Organizing Computational Biology Projects http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.100042  A must read for computational biologists!

11. Reproducibility of computational workflows is automated using continuous analysis https://www.nature.com/articles/nbt.3780

12. Five selfish reasons to work reproducibly https://genomebiology.biomedcentral.com/articles/10.1186/s13059-015-0850-7

https://www.forbio.uio.no/events/courses/2020/Bergen_Phylogenetics_2020.html

ForBio travel grants
We have changed our travel grants rules. ForBio offers both incoming and outgoing travel grants to fund collaborations between ForBio members based in Norway and taxonomic experts up to NOK 14,000. Grants are given for taxonomic training with relevance to the main research project of the applicant, and aim to allow the student to do taxonomic research with specific experts, work with particular collections, or learn new preparation techniques directly from experts.  Participation in external courses, conferences, fieldwork or other kinds of activities which are not classified as expert-in-training visits are no longer eligible for support.  There are two application deadlines: March 1st 2020.

Find the detail of the reads repeats:

fq2fa ONT_A.fastq ONT_A.fasta 

minimap2 -xava-ont ONT_A.fasta ONT_A.fasta -t10 -X > AONT.paf 

awk '{if($1==$6){print}}' AONT.paf > AONTself.paf 

awk '$5=="-"' AONTself.paf | awk '{print $1}'| sort|uniq > invertedrepeat.list

Generated a few palindrome and repeats plots (highlighting only repeats largest than 10, 20 and 30 kb)

minidot -f 5 -m 30000 AONTself.paf > AONTself30000.eps 
sed 's/_template_pass_FAH31515//' AONTself30000.eps > AONTself30000final.eps 

minidot -f 5 -m 20000 AONTself.paf > AONTself20000.eps 
sed 's/_template_pass_FAH31515//' AONTself20000.eps > AONTself20000final.eps 

minidot -f 5 -m 10000 AONTself.paf > AONTself10000.eps 
sed 's/_template_pass_FAH31515//' AONTself10000.eps > AONTself10000final.eps 

Assemble with miniasm:

miniasm -f ONT_A.fasta AONT.paf > AONT.gfa 

grep '^S' AONT.gfa |awk '{print ">"$2"\n"$3}' > AONT_miniasm.fasta 

minimap2 -xasm10 AONT_miniasm.fasta AONT_miniasm.fasta -t1 -X > AONT_miniasm.paf 

awk '{if($1==$6){print}}' AONT_miniasm.paf > AONT_miniasm_self.paf 

minidot -f 5 -m 10000 AONT_miniasm_self.paf > AONT_miniasm_self10000.eps 

Njoy the assembly !

Prerequisites

• A fresh Vultr Cloud Compute instance with Ubuntu 18.04 and root access.

Step 1: Install Apache, MySQL, and PHP

Elgg requires MySQL, PHP, and a web server. Before you can install Elgg, you will need to install the Apache web server, MySQL, and PHP.

Update the repository list.

apt-get update

Install the Apache web server.

apt-get install apache2 -y

Install MySQL.

apt-get install mysql-server -y

Complete the MySQL installation by executing the following command.

/usr/bin/mysql_secure_installation

During the installation, you will be asked to enter a root password. Enter a secure password. This will be the MySQL root password.

Would you like to setup VALIDATE PASSWORD plugin? [Y/N] N
New password: password
Re-enter new password: password
Remove anonymous users? [Y/N] Y
Disallow root login remotely? [Y/N] Y
Remove test database and access to it? [Y/N] Y
Reload privilege tables now? [Y/N] Y

Install PHP 7.2, as well as the PHP modules required by Elgg.

apt-get install php7.2 libapache2-mod-php7.2 php7.2-common php7.2-sqlite3 php7.2-curl php7.2-intl php7.2-mbstring php7.2-xmlrpc php7.2-mysql php7.2-gd php7.2-xml php7.2-cli php7.2-zip -y

Step 2: Create a MySQL database for Elgg

Elgg will require a MySQL database. Log into the MySQL console.

mysql -u root -p

When prompted for a password, enter the MySQL root password you set in step 1. Once you are logged in to the MySQL console, create a new database.

CREATE DATABASE elgg;

Create a new MySQL user and grant it privileges to the newly created database. You can replace username and password with the username and password of your choice.

GRANT ALL PRIVILEGES on elgg.* to 'username'@'localhost' identified by 'password';
FLUSH PRIVILEGES;

Exit the MySQL console.

exit

Step 3: Download and Install Elgg

Download the latest version of Elgg.

cd /var/www/html
rm -r index.html
wget https://elgg.org/download/elgg-2.3.7.zip

Unzip the downloaded archive and move the files to the root of the Apache web server.

apt install unzip
unzip elgg-2.3.7.zip
mv ./elgg-2.3.7/* . && rm elgg-2.3.7.zip && rm -r elgg-2.3.7

Create a data directory for Elgg.

sudo mkdir -p /var/www/html/data

Set the appropriate file permissions.

sudo chown -R www-data:www-data /var/www/html/
sudo chmod -R 755 /var/www/html/

Step 4: Configure Apache for Elgg

Elgg requires the Apache rewrite module. Enable the Apache rewrite module.

sudo a2enmod rewrite

Create an Apache configuration file for the Elgg installation.

sudo nano /etc/apache2/sites-available/elgg.conf

Paste the following snippet to the file, replacing example.com with your own domain name.

<VirtualHost *:80>
     DocumentRoot /var/www/html/
     ServerName example.com
     <Directory /var/www/html/>
          Options FollowSymlinks
          AllowOverride All
          Require all granted
     </Directory>
     ErrorLog ${APACHE_LOG_DIR}/error.log
     CustomLog ${APACHE_LOG_DIR}/access.log combined
</VirtualHost>

Enable the configuration and restart the Apache server.

 sudo a2ensite elgg.conf
 sudo systemctl restart apache2.service

Address of the bookmark: http://omega.omicsbio.org/

So far miniasm is in early development stage. It has only been tested on a dozen of PacBio and Oxford Nanopore (ONT) bacterial data sets. Including the mapping step, it takes about 3 minutes to assemble a bacterial genome. Under the default setting, miniasm assembles 9 out of 12 PacBio datasets and 3 out of 4 ONT datasets into a single contig. The 12 PacBio data sets are PacBio E. coli sample, ERS473430, ERS544009, ERS554120, ERS605484, ERS617393, ERS646601, ERS659581, ERS670327, ERS685285, ERS743109 and a deprecated PacBio E. coli data set. ONT data are acquired from the Loman Lab.

For a C. elegans PacBio data set (only 40X are used, not the whole dataset), miniasm finishes the assembly, including reads overlapping, in ~10 minutes with 16 CPUs. The total assembly size is 105Mb; the N50 is 1.94Mb. In comparison, the HGAP3produces a 104Mb assembly with N50 1.61Mb. This dotter plot gives a global view of the miniasm assembly (on the X axis) and the HGAP3 assembly (on Y). They are broadly comparable. Of course, the HGAP3 consensus sequences are much more accurate. In addition, on the whole data set (assembled in ~30 min), the miniasm N50 is reduced to 1.79Mb. Miniasm still needs improvements.

Miniasm confirms that at least for high-coverage bacterial genomes, it is possible to generate long contigs from raw PacBio or ONT reads without error correction. It also shows that minimap can be used as a read overlapper, even though it is probably not as sensitive as the more sophisticated overlapers such as MHAP and DALIGNER. Coupled with long-read error correctors and consensus tools, miniasm may also be useful to produce high-quality assemblies.

Minimap and miniasm are ultrafast tools for (i) mapping and (ii) assembly. Designed for long, noisy reads, they do not have a correction or consensus step, and therefore the resulting assemblies are contiguous (i.e. long) but very noisy (i.e. full of errors)

We start with an all against all comparison:

minimap -Sw5 -L100 -m0 -t8 reads.fq reads.fq | gzip -1 > reads.paf.gz

Then we can assemble

miniasm -f reads.fq reads.paf.gz > reads.gfa

Convert GFA to FASTA:

awk '/^S/{print ">"$2"\n"$3}' reads.gfa | fold > reads.fa

And then count how many contigs:

grep ">" reads.fa | wc -l

# Download sample PacBio from the PBcR website
wget -O- http://www.cbcb.umd.edu/software/PBcR/data/selfSampleData.tar.gz | tar zxf -
ln -s selfSampleData/pacbio_filtered.fastq reads.fq
# Install minimap and miniasm (requiring gcc and zlib)
git clone https://github.com/lh3/minimap && (cd minimap && make)
git clone https://github.com/lh3/miniasm && (cd miniasm && make)
# Overlap
minimap/minimap -Sw5 -L100 -m0 -t8 reads.fq reads.fq | gzip -1 > reads.paf.gz
# Layout
miniasm/miniasm -f reads.fq reads.paf.gz > reads.gfa

Address of the bookmark: https://github.com/lh3/miniasm

Address of the bookmark: https://github.com/marbl/MashMap

https://github.com/ggonnella/rgfa

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5103826/