JCVI: A Versatile Toolkit for Comparative Genomics Analysis

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

| | | | ------- | ---------------------------------------------------------------- | | Authors | Haibao Tang (tanghaibao) | | | Vivek Krishnakumar (vivekkrish) | | | Adam Taranto (Adamtaranto) | | | Xingtan Zhang (tangerzhang) | | | Won Cheol Yim (wyim-pgl) | | Email | tanghaibao@gmail.com | | License | BSD |

How to cite

[!TIP] JCVI is now published in iMeta!

Tang et al. (2024) JCVI: A Versatile Toolkit for Comparative Genomics Analysis. iMeta

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.
  • Ribbon plots from whole genome alignments.

• 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

JCVI requires Python3 between v3.9 and v3.12.

Some graphics modules require the ImageMagick library.

On MacOS this can be installed using Conda (see next section). If you are using a linux system (i.e. Ubuntu) you can install ImageMagick using apt-get:

bash sudo apt-get update sudo apt-get install libmagickwand-dev

See the Wand docs for instructions on installing ImageMagick on other systems.

A few modules may ask for locations of external programs, if the executable cannot be found in your PATH.

The external programs that are often used are:

• Kent tools
• BEDTOOLS
• EMBOSS

Managing dependencies with Conda

You can use the the YAML files in this repo to create an environment with basic JCVI dependencies.

If you are new to Conda, we recommend the Miniforge distribution.

```bash conda env create -f environment.yml

conda activate jcvi ```

Note: If you are using a Mac with an ARM64 (Apple Silicon) processor, some dependencies are not currently available from Bioconda for this architecture.

You can instead create a virtual OSX64 (intel) env like this:

```bash conda env create -f env_osx64.yml

conda activate jcvi-osx64 ```

After activating the Conda environment install JCVI using one of the following options.

Installation

Installation options

1) Use pip to install the latest development version directly from this repo.

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

2) Install latest release from PyPi.

bash pip install jcvi

3) Alternatively, if you want to install in development mode.

bash git clone git://github.com/tanghaibao/jcvi.git && cd jcvi pip install -e '.[tests]'

Test Installation

If installed successfully, you can check the version with:

bash jcvi --version

Usage

Use python -m to call any of the modules installed with JCVI.

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

```console 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:

console 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.

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