JCVI utility libraries

Collection of Python libraries to parse bioinformatics files, or perform computation related to assembly, annotation, and comparative genomics.

Citations

• If you use the MCscan pipeline for synteny inference, please cite:

  Tang et al. (2008) Synteny and Collinearity in Plant Genomes. Science

• If you use the ALLMAPS pipeline for genome scaffolding, please cite:

  Tang et al. (2015) ALLMAPS: robust scaffold ordering based on multiple maps. Genome Biology

• For other uses, please cite the package directly:

  Tang et al. (2015). jcvi: JCVI utility libraries. Zenodo. 10.5281/zenodo.31631

Contents

Following modules are available as generic Bioinformatics handling methods.

• algorithms

  • Linear programming solver with SCIP and GLPK.
  • Supermap: find set of non-overlapping anchors in BLAST or NUCMER output.
  • Longest or heaviest increasing subsequence.
  • Matrix operations.

• apps

  • GenBank entrez accession, Phytozome, Ensembl and SRA downloader.
  • Calculate (non)synonymous substitution rate between gene pairs.
  • Basic phylogenetic tree construction using PHYLIP, PhyML, or RAxML, and viualization.
  • Wrapper for BLAST+, LASTZ, LAST, BWA, BOWTIE2, CLC, CDHIT, CAP3, etc.

• formats

  Currently supports .ace format (phrap, cap3, etc.), .agp (goldenpath), .bed format, .blast output, .btab format, .coords format (nucmer output), .fasta format, .fastq format, .fpc format, .gff format, obo format (ontology), .psl format (UCSC blat, GMAP, etc.), .posmap format (Celera assembler output), .sam format (read mapping), .contig format (TIGR assembly format), etc.

• graphics

  • BLAST or synteny dot plot.
  • Histogram using R and ASCII art.
  • Paint regions on set of chromosomes.
  • Macro-synteny and micro-synteny plots.

• utils

  • Grouper can be used as disjoint set data structure.
  • range contains common range operations, like overlap and chaining.
  • Miscellaneous cookbook recipes, iterators decorators, table utilities.

Then there are modules that contain domain-specific methods.

• assembly

  • K-mer histogram analysis.
  • Preparation and validation of tiling path for clone-based assemblies.
  • Scaffolding through ALLMAPS, optical map and genetic map.
  • Pre-assembly and post-assembly QC procedures.

• annotation

  • Training of ab initio gene predictors.
  • Calculate gene, exon and intron statistics.
  • Wrapper for PASA and EVM.
  • Launch multiple MAKER processes.

• compara

  • C-score based BLAST filter.
  • Synteny scan (de-novo) and lift over (find nearby anchors).
  • Ancestral genome reconstruction using Sankoff's and PAR method.
  • Ortholog and tandem gene duplicates finder.

Applications

Please visit wiki for full-fledged applications.

Dependencies

Following are a list of third-party python packages that are used by some routines in the library. These dependencies are not mandatory since they are only used by a few modules.

• Biopython
• numpy
• matplotlib

There are other Python modules here and there in various scripts. The best way is to install them via pip install when you see ImportError.

Installation

The easiest way is to install it via PyPI:

pip install jcvi

To install the development version:

pip install git+git://github.com/tanghaibao/jcvi.git

Alternatively, if you want to install manually:

cd ~/code  # or any directory of your choice
git clone git://github.com/tanghaibao/jcvi.git
pip install -e .

In addition, a few module might ask for locations of external programs, if the extended cannot be found in your PATH. The external programs that are often used are:

• Kent tools
• BEDTOOLS
• EMBOSS

Most of the scripts in this package contains multiple actions. To use the fasta example:

Usage:
    python -m jcvi.formats.fasta ACTION


Available ACTIONs:
          clean | Remove irregular chars in FASTA seqs
           diff | Check if two fasta records contain same information
        extract | Given fasta file and seq id, retrieve the sequence in fasta format
          fastq | Combine fasta and qual to create fastq file
         filter | Filter the records by size
         format | Trim accession id to the first space or switch id based on 2-column mapping file
        fromtab | Convert 2-column sequence file to FASTA format
           gaps | Print out a list of gap sizes within sequences
             gc | Plot G+C content distribution
      identical | Given 2 fasta files, find all exactly identical records
            ids | Generate a list of headers
           info | Run `sequence_info` on fasta files
          ispcr | Reformat paired primers into isPcr query format
           join | Concatenate a list of seqs and add gaps in between
     longestorf | Find longest orf for CDS fasta
           pair | Sort paired reads to .pairs, rest to .fragments
    pairinplace | Starting from fragment.fasta, find if adjacent records can form pairs
           pool | Pool a bunch of fastafiles together and add prefix
           qual | Generate dummy .qual file based on FASTA file
         random | Randomly take some records
         sequin | Generate a gapped fasta file for sequin submission
       simulate | Simulate random fasta file for testing
           some | Include or exclude a list of records (also performs on .qual file if available)
           sort | Sort the records by IDs, sizes, etc.
        summary | Report the real no of bases and N's in fasta files
           tidy | Normalize gap sizes and remove small components in fasta
      translate | Translate CDS to proteins
           trim | Given a cross_match screened fasta, trim the sequence
      trimsplit | Split sequences at lower-cased letters
           uniq | Remove records that are the same

Then you need to use one action, you can just do:

python -m jcvi.formats.fasta extract

This will tell you the options and arguments it expects.

Feel free to check out other scripts in the package, it is not just for FASTA.