All Projects → tseemann → Sixess

tseemann / Sixess

Licence: gpl-3.0
🔬🐛 Rapid 16s rRNA identification from isolate FASTQ files

Programming Languages

shell
77523 projects

Labels

Projects that are alternatives of or similar to Sixess

Pyfaidx
Efficient pythonic random access to fasta subsequences
Stars: ✭ 307 (+2092.86%)
Mutual labels:  genomics
Goatools
Python library to handle Gene Ontology (GO) terms
Stars: ✭ 415 (+2864.29%)
Mutual labels:  genomics
Vg
tools for working with genome variation graphs
Stars: ✭ 710 (+4971.43%)
Mutual labels:  genomics
Megahit
Ultra-fast and memory-efficient (meta-)genome assembler
Stars: ✭ 343 (+2350%)
Mutual labels:  genomics
Bwa Mem2
The next version of bwa-mem
Stars: ✭ 408 (+2814.29%)
Mutual labels:  genomics
Deeptools
Tools to process and analyze deep sequencing data.
Stars: ✭ 448 (+3100%)
Mutual labels:  genomics
Arvados
An open source platform for managing and analyzing biomedical big data
Stars: ✭ 274 (+1857.14%)
Mutual labels:  genomics
Fermi2
Stars: ✭ 23 (+64.29%)
Mutual labels:  genomics
Vcflib
C++ library and cmdline tools for parsing and manipulating VCF files
Stars: ✭ 414 (+2857.14%)
Mutual labels:  genomics
Hail
Scalable genomic data analysis.
Stars: ✭ 706 (+4942.86%)
Mutual labels:  genomics
Bowtie2
A fast and sensitive gapped read aligner
Stars: ✭ 365 (+2507.14%)
Mutual labels:  genomics
Jcvi
Python library to facilitate genome assembly, annotation, and comparative genomics
Stars: ✭ 404 (+2785.71%)
Mutual labels:  genomics
Ncbi Genome Download
Scripts to download genomes from the NCBI FTP servers
Stars: ✭ 494 (+3428.57%)
Mutual labels:  genomics
Jvarkit
Java utilities for Bioinformatics
Stars: ✭ 313 (+2135.71%)
Mutual labels:  genomics
Galaxy
Data intensive science for everyone.
Stars: ✭ 812 (+5700%)
Mutual labels:  genomics
Gwa tutorial
A comprehensive tutorial about GWAS and PRS
Stars: ✭ 303 (+2064.29%)
Mutual labels:  genomics
Biojava
📖🔬☕️ BioJava is an open-source project dedicated to providing a Java library for processing biological data.
Stars: ✭ 434 (+3000%)
Mutual labels:  genomics
Tiledb Vcf
Efficient variant-call data storage and retrieval library using the TileDB storage library.
Stars: ✭ 26 (+85.71%)
Mutual labels:  genomics
Bgdata
A Suite of Packages for Analysis of Big Genomic Data
Stars: ✭ 19 (+35.71%)
Mutual labels:  genomics
Nucleus
Python and C++ code for reading and writing genomics data.
Stars: ✭ 657 (+4592.86%)
Mutual labels:  genomics

Build Status License: GPL v3

⚠️ THIS SOFTWARE IS STILL UNDER DEVELOPMENT - USE AT OWN RISK

sixess

Rapid 16s rDNA from isolate FASTQ files

Introduction

sixess is a command-line software tool to identify bacterial species based on 16S rDNA sequence directly from WGS FASTQ data. It includes databases from NCBI (default), RDP and SILVA.

Quick start

# just give it sequences!
% sixess R1.fastq.gz
Staphylococcus epidermidis

# sometimes there is no match
% sixess /dev/null
No matches

# give it as many sequence files as needed
% sixess R1.fq R2.fq
Enterococcus faecium

# we provide different databases you can choose
% sixess -d RDP contigs.fa
Bacillus cereus

# you can pipe to stdin too
% bzcat chernobyl.fq.bz2 | sixess -
Deinococcus radiodurans

Installation

Source

cd $HOME
git clone https://github.com/tseemann/sixess
export PATH=$HOME/sixess/bin:$PATH

Homebrew

brew install brewsci/bio/sixess  # COMING SOON

Bioconda

conda install -c bioconda -c conda-forge sixess  # COMING SOON

Usage

Input

The input can be one or more sequence files, or - denoting stdin. The input data can be FASTQ or FASTA, and may be .gz compressed. Any read length is accepted, even whole chromosomes.

Output

The output is a single line to stdout. If a match was found, it will be Genus species. If no prediction could be made, it will be No matches.

Options

  -q        Quiet mode, no output
  -p DIR    Database folder (/home/tseemann/git/sixess/db)
  -d FILE   Database {NCBI RDP SILVA.gz} (NCBI)
  -t NUM    CPU threads (1)
  -m FILE   Save alignments to FILE in PAF format
  -V        Print version and exit
  • -q enables "quiet mode" which only prints to stderr for errors
  • -p is the location of the sequence databases
  • -d selects the database; they can be .gz compressed (see Databases
  • -t increases threads; 3 is the suggested value for minimap2
  • -m allows you to save the PAF output of minimap2
  • -V prints the version and exits e.g. sixess 1.0

Databases

NCBI (bundled, default)

The NCBI 16S ribosomal RNA project contains curated 16S ribosomal RNA bacteria and archaea RefSeq entries. It has ~20,000 entries.

esearch -db nucleotide -query '33175[BioProject] OR 33317[BioProject]' \
  | efetch -db nuccore -format fasta \
  > $(which sixess)/../db/NCBI

RDP (bundled)

Bacterial 16S rDNA sequences for "type strains" from the RDP database are included. These are denoted with (T) in the FASTA headers. It contains ~10,000 entries.

wget --no-check-certificate https://rdp.cme.msu.edu/download/current_Bacteria_unaligned.fa.gz
gunzip -c current_Bacteria_unaligned.fa.gz \
  | bioawk -cfastx '/\(T\)/{print ">" $name " " $comment "\n" toupper($seq)}' \
  > $(which sixess)/../db/RDP

SILVA (bundled)

SILVA is a comprehensive on-line resource for quality checked and aligned ribosomal RNA sequence data. The filtered version of the aligned 16S/18S/SSU database contains ~100,000 entries.

# replace "132" with latest version as needed
wget https://www.arb-silva.de/fileadmin/silva_databases/release_132/Exports/SILVA_132_SSURef_Nr99_tax_silva.fasta.gz
gunzip -v SILVA_132_SSURef_Nr99_tax_silva.fasta.gz \
  | bioawk -cfastx \
    '$comment ~ /^Bacteria;|^Archaea;/ \
    && $comment !~ /(;unidentified|Mitochondria;|;Chloroplast|;uncultured| sp\.)/ \
    { sub(/^.*;/,"",$comment);
      gsub("U","T",$seq);
      print ">" $name " " $comment "\n" $seq }' \
  | seqtk seq -l 60 -U \
  > SILVA.tmp1
cd-hit-est -i SILVA.tmp1 -o SILVA.tmp2 -c 1.0 -T 0 -M 2000 -d 250
cp SILVA.tmp2 $(which sixess)/../db/SILVA
rm -f SILVA.tmp1 SILVA.tmp2 SILVA.tmp2.clstr

Custom databases

Assuming you have a FASTA file of 16S DNA sequences called /home/alex/GG.fa say, you can do this:

Global installaion

cp /home/alex/GG.fa $(which sixess)/../db/GG
sixess -d GG R1.fastq.gz

Local installaion

sixess -p /home/alex/data -d GG.fa R1.fastq.gz

Algorithm

  1. Identify reads which look like 16S (minimap2)
  2. Count up how many reads hit each 16S sequence (possibly weighted)
  3. Choose the top hit and report it

Feedback

Report bugs and give suggesions on the Issues page

License

GPL Version 3

Author

Torsten Seemann

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].