A Python toolkit for the statistical and visualization of core and pan genes in Pan-genome
Project description
PanStat: A Python toolkit for the statistical and visualization of core and pan genes in Pan-genome
Installation
python3 -m pip install panstat
Usage
panstat -h
1. stat
Usage: panstat stat [OPTIONS]
Calculate statistics for core and pan genes
Options:
-i, --input-file PATH Path to the input data file [required]
-o, --output-file PATH Path where the results will be saved [default: output_stat.txt]
-n, --num-samples INTEGER Number of samples to compute [required]
-t, --share_type [intersection|union]
Type of share to compute
--header INTEGER Row number to use as the column names [default: 0]
--sep TEXT Delimiter to use for reading the input file (e.g., "\t" for tab)
--start-col INTEGER Column index to start reading sample data from [default: 1]
--show-progress BOOLEAN Show progress
--chunksize INTEGER The chunksize lines to read
--chunk INTEGER The index of chunk
-h, -?, --help Show this message and exit.
examples:
panstat stat -h
panstat stat -i input.txt -o output.txt -n 13 -t intersection
panstat stat -i input.txt -o output.txt -n 13 -t intersection --chunksize 100 --chunk 2 [read 101-200 lines]
2. plot
Usage: panstat plot [OPTIONS] RESULT_DIR
Generate Boxplot with statistics results
Options:
-R, --Rscript TEXT Path to the executable Rscript [default: Rscript]
-w, --write TEXT Write the R code to a file
--option TEXT Options in the format key=value for boxplot, eg. title="Demo Stats", x_lab="Shared_Numbers",
y_lab="Data"
-h, -?, --help Show this message and exit.
examples:
panstat plot -h
panstat plot out/result
panstat plot out/result --write boxplot.R
panstat plot out/result --write boxplot.R --option x_lab=XXX --option width=30 --option dpi=500
default options:
infile = 'processed_stats.tsv'
output = 'boxplot'
x_lab = 'Genomes'
y_lab = 'Families'
title = 'BoxPlot'
legend_title = 'Type'
dpi = 300
width = 14
height = 7
3. batch
Usage: panstat batch [OPTIONS]
Generate batch shells and SJM job
Options:
-i, --input-file PATH Path to the input data file
-sep, --sep TEXT Delimiter to use for reading the input file (e.g., "\t" for tab)
-s, --start-col INTEGER Column index to start reading sample data from [default: 1]
-t, --threshold INTEGER The threshold to divide the combinations [default: 200000]
-O, --output-dir PATH Path to the output directory [default: .]
--job TEXT Generate SJM Job
--no-check Do not check queues for SJM
-h, -?, --help Show this message and exit.
examples:
panstat batch -h
panstat batch -i input.txt -t 200000 -O out
panstat batch -i input.txt -t 200000 --job run.job
Result
prefix
- x: core genes (intersection)
- y: pan genes (union)
shell directory
shell/
├── plot.sh
├── x2
│ └──stat.x2_1.sh
├── y2
│ └──stat.y2_1.sh
...
├── x14
│ ├── stat.x14_1.sh
│ ├── stat.x14_2.sh
│ ├── ...
│ └── stat.x14_100.sh
...
└── y29
└──stat.y29_1.sh
statistical result
result/
├── x2
│ └──x2_1.txt
├── y2
│ └──y2_1.txt
...
├── x14
│ ├── x14_1.txt
│ ├── x14_2.txt
│ ├── ...
│ └── x14_100.txt
...
└── y29
└──y29_1.txt
visualization result
processed_stats.tsv
plot.R
pointplot.png
pointplot.pdf
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
panstat-1.0.4.tar.gz
(13.7 kB
view details)
Built Distribution
panstat-1.0.4-py3-none-any.whl
(17.4 kB
view details)
File details
Details for the file panstat-1.0.4.tar.gz
.
File metadata
- Download URL: panstat-1.0.4.tar.gz
- Upload date:
- Size: 13.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.8.8
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0f0a0e880c0156782483efd677817d4fb7dea6ecb8376893c506af2625cde2d1 |
|
MD5 | 3627692c1fd003c88fa9c92e63463cce |
|
BLAKE2b-256 | f4a18e09fcca63a6674da6a8f104f4e2a3de1911427e7eefc5101ad1073e3d0b |
File details
Details for the file panstat-1.0.4-py3-none-any.whl
.
File metadata
- Download URL: panstat-1.0.4-py3-none-any.whl
- Upload date:
- Size: 17.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.8.8
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | f2e151298ca31aeb111ee4764998934d18c299a19d0a14cc91dd6f059953f48e |
|
MD5 | 7c6d847802395a49ba5028aa157abfd2 |
|
BLAKE2b-256 | c56b933c6f44fea4704e8e43a885bcf171edbbaba8eaa975f5a042ca21803298 |