Skip to main content

CPStools is a package for analyzing chloroplast genome sequences.

Project description

CPStools Usage

Install

# python version >= 3.9
pip install biopython 
# 使用清华源安装 python version >= 3.9
pip install cpstools -i  https://pypi.tuna.tsinghua.edu.cn/simple

Usage

cpstools -h 

subcommand

gbcheck

gbcheck subcommand accepts two parameters:

-i, --test_file

-r, --ref_file

The parameter of -i/--test_file is required, and -r/--ref_file is optional.

If only -i/--TEST_FILE, the gbcheck.py will check the annotation of the input file. The script will check the gene name in each gene, CDS, tRNA and rRNA. For CDS, tRNA and rRNA, it will also check the 'product' label.

For CDS, the codon amino acids will be check, if start codon, stop codon and internal codon was wrong, it will print out the location of CDS.

# self check
cpstools gbcheck -i input_file
# compara
cpstools gbcheck -i input_file -r ref_file

info

info subcommand accepts one parameter:

-i, --input_file

The parameter of -i/-input_file

This subcommand is used to statistic the gene types and gene numbers

cpstools info -i input_file 

IR

IR subcommand accepts one parameter:

-i, --input_file

The parameter of -i/--input_file is required, and the input file can be genbank/fasta format. It will find the four regions in the chloroplast sequences, which the IR region will be identified if length surpass 1,000 bp.

cpstools IR -i input_file

Seq

The Seq subcommand can be used to adjust the start to the 1st bp in LSC region and the SSC forward. This analysis should combine with the co-linearity.

Seq subcommand accepts four parameter:

-d, --work_dir

The parameter of -i/--work_dir is required, and the input directory is fasta format of all need adjusted sequences.

-f, --info_file The parameter offile of -f/--info_file is required, This file can be generated from IR subcommand.

-m {SSC,LSC,RP}, --mode {SSC,LSC,RP}

The parameter of -m is also required, And three choices was supported: Mode: SSC for adjust_SSC_forward, LSC foradjust_start_to_LSC, RP for adjust sequence to reverse_complement

# adjust to LSC 1 bp start, the results are saved in LSC directory
cpstools Seq -d work_dir  -f info.txt -m LSC

# adjust SSC forward, the results are saved in SSC directory
cpstools Seq -d work_dir  -f info.txt -m SSC

# adjust to reversed complement and LSC 1 bp start, the results are saved in RP directory
cpstools Seq -d work_dir  -f info.txt -m RP

Pi

The Pi subcommand accepts a required parameter -d/--work_dir and an optional parameter -m/--mafft_path. It automatically extracts shared gene regions and shared intergenic sequences from gb files in the work_dir, performs multiple sequence alignments, and calculates Pi values. Finally, it outputs the results sorted according to the chloroplast genome order.

# If mafft in the environment variables
cpstools Pi -d work_dir

# if mafft not in the environment variables
cpstools Pi -d work_dir -m mafft_path

RSCU

The RSCU subcommand accepts a required parameter -d/--work_dir and an optional parameter -l/--filter_length. It automatically extracts shared coding regions from GenBank files in the work_dir, removes duplicates, filters out short sequences, and calculates their RSCU values.

# filter_length default is 300 bp
cpstools RSCU -d work_dir 
# filter_length is n bp
cpstools RSCU -d work_dir -l n

SSRs

The SSRs subcommand accepts a required parameter -i/--input_file and an optional parameter -k/--kmer_length. It automatically identifies and locates SSRs in the GenBank files.

# SSRs length, default is 10,6,5,4,4,4
cpstools SSRs -i input_file 
# SSRs length set to a specified length, 10,5,4,3,3,3
cpstools SSRs -i input_file -k 10,5,4,3,3,3

converse

The converse subcommand accepts two required parameter -d/--input_dir and -m/--mode {fasta,mVISTA,tbl}. It automatically converse genbank format file into fasta/mVISTA/tbl format.

# converse genbank into fasta, the output in the fasta directory
cpstools converse -d input_dir -m fasta

# converse genbank into tbl, the output in the tbl directory
cpstools converse -d input_dir -m tbl

# converse genbank into mVISTA, the output in the mVISTA directory
cpstools converse -d input_dir -m mVISTA

LSRs

The LSRs subcommand accepts one required parameter -i/--input_file . It automatically reads the output results from Reputer, sorts, and locates them.

cpstools LSRS -i input_file

phy

The phy subcommand accepts two required parameter -d/--input_dir and -m/--mode {cds,pro}. It automatically extracts shared CDS or protein sequences from GenBank files in the input_dir, sorts, and merges them.

# to extract shared CDS sequences for phylogenetic analysis
cpstools phy -d input_dir -m cds

# to extract shared protein sequences for phylogenetic analysis
cpstools phy -d input_dir -m pro

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cpstools-2.0.2.tar.gz (29.4 kB view details)

Uploaded Source

Built Distribution

cpstools-2.0.2-py3-none-any.whl (37.8 kB view details)

Uploaded Python 3

File details

Details for the file cpstools-2.0.2.tar.gz.

File metadata

  • Download URL: cpstools-2.0.2.tar.gz
  • Upload date:
  • Size: 29.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.12.4 Darwin/23.6.0

File hashes

Hashes for cpstools-2.0.2.tar.gz
Algorithm Hash digest
SHA256 7be13651918b295af3f11288208b41b7c511ccb0c8b65b09150c0bf687f1e0bc
MD5 f4f42531f17d6a8eedb92d028cc24846
BLAKE2b-256 13ed01d44bb8edd5afcf7ba42ba93b3d51e100c994b154380ed9467ae1e9925d

See more details on using hashes here.

File details

Details for the file cpstools-2.0.2-py3-none-any.whl.

File metadata

  • Download URL: cpstools-2.0.2-py3-none-any.whl
  • Upload date:
  • Size: 37.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.12.4 Darwin/23.6.0

File hashes

Hashes for cpstools-2.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 4b3428657627e5c8bbaaf4add2e168fd5e92cce3189df694602962fd5540f94c
MD5 e6f96789308b6b0c8a12b8e37ba9282e
BLAKE2b-256 fdff289b40a99a8dac2ac581c034702db601edff776a8697653cdf21f89ef66f

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page