Brivez is a bioinformatic tool thought as Quality of Life's improvement, providing high quantity of data in a snap, giving you a quick view on what you could find inside your transcriptome/sequences' list.

Installation requirements aside, you will need two files:

• domain_profile.hmm
  It goes inside --> 01_hmm_profiles folder
• sequence(s).fasta
  It goes inside --> 02_fasta_target

Suggested way to proceed:

1. Read the documentation
2. The first time follow the checklist
3. Run ./brivez_main.sh

At the moment this program runs exclusively on Linux (tested on Debian 11 and Ubuntu 22.04).

See future updates for Mac and Windows.

All the software used are OpenSource.

• Workflow
  
• Software requirements
  
• Quickly set up
  
• First run
  
• Read results
  
• Useful link
  
• Future updates
  

Brivez analyses every fasta file insiede 02_fasta_target.
Every single run follow these workflow:

• Runs Deepsig looking for Signal Peptide (can be disabled with -a)
• Uses the sequences found in the previously step
• Searches for domains using the hmm file inside 01_hmm_profiles
  • If Brivez founds more than one hmm file, it asks which one choose
• Generates multiple output files for each fasta target
  • A file with all the domain extraced can be genereted with -b option

• Conda (minimum ~3 GB)
• Environment inside Conda with:
  • Deepsig (~50 MB) --> needs PYTHON 3.8 !
  • Pandas (~15 MB)
  • Bio-conda (channel)
  • fnmatch (samtools ~1 MB)
• HMMER3 v3.3.2 (~20 MB)
• Brivez (~1 MB)

01 - Quick install for Conda (following the online doc is suggested):

1. Download the installer at this link
2. Verify your installer hashes
3. In the terminal run
   bash Anaconda-latest-Linux-x86_64.sh
   Create an environment ad hoc
   conda create -n bioinfo-brivez python=3.8
   To see all the env created
   conda env list
4. Choose the environment with
   conda activate bioinfo-brivez
   to close it use
   conda deactivate bioinfo-brivez

---- By this point be sure to have activated the right environment! ----

02 - Install in Conda some stuff:

• conda config --add channels bioconda
  
• conda install -c bioconda samtools
  
• conda install -c conda-forge dpath
  
• conda install pandas

03 - Install the predictor of signal peptides, DeepSig

• Just as described on its site, use
  conda install -c bioconda deepsig

04 - Install HMMER3

• Just as described on its site, use
  sudo apt-get install hmmer
  (v3.3.2 both on Ubuntu 22.04 and Debian 11)
  Otherwise is installable following the official documentation

05 - Download Brivez

• Download the Brivez folder with
  git clone https://github.com/furacca/brivez
  or whatever way you prefer

1. 01_hmm_profiles

   • contains your hmm files (check hmm - Pfam download)

2. 02_fasta_target

   • contains your fasta files
   • the only accepted format is fasta (no fas, fa, ...)

3. Be sure to have the right environment activated
   

   • conda activate therightenvironment

4. Run Brivez with
   ./brivez_main.sh

Inside the 03_results you will have your output folder, all with the same structure:

• Research_number_XXX
  • fasta_target1 (directory)
    • multiples files
  • fasta targetX (directory)
    • multiples files
  • Report (file)

For every fasta target there will be one folder containings the following:

• 01_deepsig-analysis.tsv
  • Deepsig analysis; if -a is enabled, then is empty
• 02_sequences_selected.fasta
  • Sequences with SP by deepsig; if -a is enabled, all sequences are selected
• 03_hmmsearch_output_table
  • hmmsearch output
• 04_hmmsearch_output_table_data_parsed
  • hmmsearch output parsed in csv
• 05_pandas_sequences_table.tsv
  • pandas table with the list of all domains found
• 06_sequences_which_have_domains.fasta
  • list of sequences presenting domains found
• 07_extracted_domains.fasta
  • domains found extracted by the selected sequences
• 08_extracted_domains.csv
  • same as 07, but in csv format
• 09_domains_found.csv

Important The 08_extracted_domains.csv file can be easyly read in calc/excel selecting all the cells and clicking on Data -> Autofilters.

• hmm - Pfam download
  Contains tutorials on:
  • How to download the full Pfam database
  • How to download a specific ~.hmm file from pfam
• Hmmer cheatsheet

None (yet).

TOP PRIORITY

• None

MEDIUM PRIORITY

• Simpler way to user Brivez (Docker? Appimage?)
• List of the sequences with just one domain type (needing full Pfam database)

LOW PRIORITY

• Check some solution for Mac and Windows (Docker?)
• Extracted list of all SP