Find binding specificity information about DNA-protein complexes.

Find information about the binding specificity of DNA-binding proteins.

Predict interacting partners and binding models.

Use this web-based sequence motif visualization system to display sequence motif information in its appropriate three-dimensional (3D) context.

Protein function prediction and annotation in an integrated environment powered by web service.

Find information about protein binding.

Use to predict function from de novo protein sequences.

Search for short active protein sequences with demonstrated biological activities.

Search for ungapped segments corresponding to the most highly conserved regions of proteins.

Identify and measure surface accessible pockets as well as interior inaccessible cavities, for proteins and other molecules.

To search for catalytic residue annotation for enzymes in the Protein Data Bank.

Predict protein function using Gene Ontology.

Automatically calculate evolutionary conservation scores of key amino acid residues and map them on protein structures.

Mine the protein structure space.

Predict short linear motifs (3-8 residues) in a set of protein sequences.

A web client for visualizing protein sequence feature information using DAS.

Identify the domain architecture within a protein sequence.

Predict enzyme catalytic site.

Predict functional sites in eukaryotic proteins.

Use a collection of tools for protein analyses.

Predict potential protein post-translational modifications and find potential single amino acid substitutions in peptides.

Search for information related to the catalytic mechanisms of enzymes.

An integrated feature-based function prediction server for vertebrate proteomes.

Identify the closest matching PRINTS sequence motif fingerprints in a protein sequence.

Search for functional annotation of important sites in proteins with known structures.

Produce 3D conformations of small drug compounds.

A database presenting experiment-based results in human proteomics.

Conduct exhaustive intermediate profile searches of a set of homologous protein sequences.

Design protein mutations in site-directed mutagenesis.

Use for protein functional site identification.

Annotate protein using this integrated annotation resource.

Identify protein family (and DNA) domains, patterns, motifs, protein families, and functional sites.

Interactive forecasting of protein interaction hot spots.

Discover long patterns in protein sequences.

Database containing pairs of structural analogs and their alignments.

Find sequence patterns in DNA and protein sequences.

A web server for knowledge-based modeling of protein-peptide complexes, specifically peptides in complex with major histocompatibility complex (MHC) proteins and kinases.

Predict protein methylation sites.

Find structural segments or motifs for protein structures.

Find motifs in a protein sequence.

Visualize protein sequence motifs on the 3D protein structures.

Find presence of any known protein motif (Prosite and Pfam) in a protein sequence.

Recognize spatial chemical binding patterns common to a set of protein structures.

Analyze proteins for the presence of N-terminal N-myristoylation site.

Find the presence of N-Glycosylation sites in human proteins.

Find the presence of O-GalNAc (mucin type) glycosylation sites in mammalian proteins.

Analyze eukaryotic proteins for the presence of serine, threonine and tyrosine phosphorylation sites.

Find possible kinase specific phosphorylation sites in eukaryotic proteins.

Predict cleavage sites at basic amino acid locations in neuropeptide precursor sequences.

Find information about patented nucleotide and protein sequences.

Search for information about glycoproteins with O-linked and C-linked glycosylation sites.

Find information about protein sequence annotations.

A server to predict protein active site residues.

Search for structural and functional information on the protein functional sites.

Search 3D protein fragments similar in structure to known active, binding and posttranslational modification sites.

Conduct genome wide functional and structural analysis.

Search for phosphorylation data of any protein of interest.

Search for information on prokaryotic proteins that undergo serine, threonine, or tyrosine phosphorylation.

Determine correct names for proteins.

Web application for predicting protein disorder by using physicochemical features and reduced amino acid set of a position-specific scoring matrix.

Find homologous protein-protein interactions across multiple species.

Search your query sequence against PROSITE pattern database for protein motifs.

Find information about protein-RNA complexes from the Protein Data Bank (PDB).

Search for protein fingerprints.

Identify protein families and domains for a given protein sequence.

A comprehensive database of pattern-recognition receptors and their ligands.

Search for short nucleotide or peptide sequences such as cis-elements in nucleotide sequences or small domains and motifs in protein sequences.

Database specialized in documenting human PPBD-containing proteins and PPBD-mediated interactions.

Predicts potential protease cleavage sites and sites cleaved by chemicals in a given protein sequence.

Predict combined transmembrane topology and signal peptides.

Search for eukaryotic phosphorylation sites.

Search for 3D structure and functional annotation of phosphorylation sites in proteins.

Search the database of in vivo phosphorylation sites of human and mouse proteins

Find information about polyglutamine (polyQ) repeats.

Find the presence of protein motifs and patterns in an amino acid sequence.

Predict signal peptide sequences and their cleavage positions in bacterial and eukaryotic amino acid sequences.

Predict protein functions based on known structures.

Predict the location of potential protein-protein binding sites for unbound proteins.

Identify short linear signatures in protein termini.

Analyze and identify newly obtained protein sequences.

Predict protein binding sites in a protein sequence based on geometrical analysis of protein tertiary substructures.

Search for evolutionarily conserved motif-like patterns in protein sequences.

Web-based server for analyzing and predicting RNA binding sites in proteins.

Search for similarities between proteins by simultaneous matching of multiple motifs.

Predict residues in protein sequences that determine the proteins' functional specificity.

Predict specificity-determining residues in protein families.

Find shared motifs in proteins with a common attribute.

Conduct in silico sumoylation sites prediction.

Detect protein sequence section under positive evolution selection.

Search for motifs and patterns within protein sequences.

Detect patterns, profiles and motifs in a protein sequence.

Search for motifs within proteins that are likely to be phosphorylated by specific protein kinases or bind to domains such as SH2 domains, 14-3-3 domains or PDZ domains.

Find information about populations carrying polymorphisms within protein binding pockets that make them susceptible to serious adverse drug reaction (SADR).

Search the presence of a motif in either amino acid sequence or nucleotide sequence.

Predict signal peptides.

Predict signal peptides and their cleavage sites.

Predict the presence of tyrosine sulfation sites in protein sequences

Look at protein structure from a ligand and binding site perspective.

Use a collection of bioinformatics tools at this portal site.

Find information about tandem repeats in proteins that carry fundamental biological functions and are related to a number of human diseases.

Find information about functional residues in alpha-helical and beta-barrel membrane proteins.

Database of domains and motifs with conservative location in transmembrane proteins.

Search for highly conserved and specific protein sequence motifs.

Predict functional sites in protein sequence alignments use different methodologies.

Find de novo protein motifs from chromatin immunoprecipitation data.

Scan query structures for functional sites in both proteins and nucleic acids.

Analyze quantitative structure-activity relationship of related protein families.

Search for ungapped alignments of highly conserved regions among a protein family or superfamily.

Predict the functional sites of proteins.

An expert system for predicting ligand-binding residues in protein structures.

Automatically identify spatially interacting motifs among distantly related proteins sharing similar folds and possessing common ancestral lineage.

spades.py

SPAdes genome assembler v3.10.1

Usage: /usr/local/SPAdes-3.10.1-Linux/bin/spades.py [options] -o <output_dir>

Basic options:
-o      <output_dir>    directory to store all the resulting files (required)
--sc                    this flag is required for MDA (single-cell) data
--meta                  this flag is required for metagenomic sample data
--rna                   this flag is required for RNA-Seq data
--plasmid               runs plasmidSPAdes pipeline for plasmid detection
--iontorrent            this flag is required for IonTorrent data
--test                  runs SPAdes on toy dataset
-h/--help               prints this usage message
-v/--version            prints version

Input data:
--12    <filename>      file with interlaced forward and reverse paired-end reads
-1      <filename>      file with forward paired-end reads
-2      <filename>      file with reverse paired-end reads
-s      <filename>      file with unpaired reads
--pe<#>-12      <filename>      file with interlaced reads for paired-end library number <#> (<#> = 1,2,..,9)
--pe<#>-1       <filename>      file with forward reads for paired-end library number <#> (<#> = 1,2,..,9)
--pe<#>-2       <filename>      file with reverse reads for paired-end library number <#> (<#> = 1,2,..,9)
--pe<#>-s       <filename>      file with unpaired reads for paired-end library number <#> (<#> = 1,2,..,9)
--pe<#>-<or>    orientation of reads for paired-end library number <#> (<#> = 1,2,..,9; <or> = fr, rf, ff)
--s<#>          <filename>      file with unpaired reads for single reads library number <#> (<#> = 1,2,..,9)
--mp<#>-12      <filename>      file with interlaced reads for mate-pair library number <#> (<#> = 1,2,..,9)
--mp<#>-1       <filename>      file with forward reads for mate-pair library number <#> (<#> = 1,2,..,9)
--mp<#>-2       <filename>      file with reverse reads for mate-pair library number <#> (<#> = 1,2,..,9)
--mp<#>-s       <filename>      file with unpaired reads for mate-pair library number <#> (<#> = 1,2,..,9)
--mp<#>-<or>    orientation of reads for mate-pair library number <#> (<#> = 1,2,..,9; <or> = fr, rf, ff)
--hqmp<#>-12    <filename>      file with interlaced reads for high-quality mate-pair library number <#> (<#> = 1,2,..,9)
--hqmp<#>-1     <filename>      file with forward reads for high-quality mate-pair library number <#> (<#> = 1,2,..,9)
--hqmp<#>-2     <filename>      file with reverse reads for high-quality mate-pair library number <#> (<#> = 1,2,..,9)
--hqmp<#>-s     <filename>      file with unpaired reads for high-quality mate-pair library number <#> (<#> = 1,2,..,9)
--hqmp<#>-<or>  orientation of reads for high-quality mate-pair library number <#> (<#> = 1,2,..,9; <or> = fr, rf, ff)
--nxmate<#>-1   <filename>      file with forward reads for Lucigen NxMate library number <#> (<#> = 1,2,..,9)
--nxmate<#>-2   <filename>      file with reverse reads for Lucigen NxMate library number <#> (<#> = 1,2,..,9)
--sanger        <filename>      file with Sanger reads
--pacbio        <filename>      file with PacBio reads
--nanopore      <filename>      file with Nanopore reads
--tslr  <filename>      file with TSLR-contigs
--trusted-contigs       <filename>      file with trusted contigs
--untrusted-contigs     <filename>      file with untrusted contigs

Pipeline options:
--only-error-correction runs only read error correction (without assembling)
--only-assembler        runs only assembling (without read error correction)
--careful               tries to reduce number of mismatches and short indels
--continue              continue run from the last available check-point
--restart-from  <cp>    restart run with updated options and from the specified check-point ('ec', 'as', 'k<int>', 'mc')
--disable-gzip-output   forces error correction not to compress the corrected reads
--disable-rr            disables repeat resolution stage of assembling

Advanced options:
--dataset       <filename>      file with dataset description in YAML format
-t/--threads    <int>           number of threads
                                [default: 16]
-m/--memory     <int>           RAM limit for SPAdes in Gb (terminates if exceeded)
                                [default: 250]
--tmp-dir       <dirname>       directory for temporary files
                                [default: <output_dir>/tmp]
-k              <int,int,...>   comma-separated list of k-mer sizes (must be odd and
                                less than 128) [default: 'auto']
--cov-cutoff    <float>         coverage cutoff value (a positive float number, or 'auto', or 'off') [default: 'off']
--phred-offset  <33 or 64>      PHRED quality offset in the input reads (33 or 64)
                                [default: auto-detect]

spades.py -t 4 \
          -m 32 \
          -k 31,51,71 \
          --only-assembler \
          -1 miseq.1.fastq -2 miseq.2.fastq \
          --nanopore minion.fastq \
          -o hybrid_assembly