volcanoPlot 0.0.2

creating a volcano plot in python for the given data, and save it as a png file.

volcanoPlot

This file will become your README and also the index of your documentation.

Install

pip install volcanoPlot

How to use

Example

Description:
RSV or RS virus, short for respiratory syncytial virus, is a single-stranded RNA virus belonging to the pneumovirus genus of the virus family.
Symptoms are usually mild, similar to a cold, but can cause very serious illness in infants.

Dataset:
We prepared a total of 8 RNA-Seq data from acute and chronic phases in nasal samples of 4 infants
The dataset was taken from Kaggle using the following API command:
kaggle datasets download -d yoshifumimiya/rsv-rnaseq-count

import pandas as pd
from pathlib import Path
df = pd.read_csv(Path.cwd() / 'res_example.csv')
df.head()

<style scoped> .dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; } </style>

	gene_id	baseMean	log2FC	lfcSE	stat	p_value	p_adj	log10p	sig	regulated
0	WASH7P	4.587857	2.458706	1.116766	2.201630	0.027691	0.202064	1.557654	True	lfc2 and p_value
1	LOC729737	122.155762	1.342039	0.716822	1.872207	0.061178	0.309724	1.213405	False	non-sig
2	TGIF1	1400.037490	-0.099168	0.142399	-0.696411	0.486171	0.796121	0.313211	False	non-sig
3	PRDX6	4794.111981	-0.008120	0.200802	-0.040440	0.967742	0.991057	0.014240	False	non-sig
4	CIC	1581.916300	0.053769	0.177791	0.302430	0.762324	0.925608	0.117860	False	non-sig

from volcanoPlot.volcano import *
plot(df=df,x='log2FC', y ='log10p')

df

<style scoped> .dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; } </style>

	gene_id	baseMean	log2FC	lfcSE	stat	p_value	p_adj	log10p	sig	regulated
0	WASH7P	4.587857	2.458706	1.116766	2.201630	0.027691	0.202064	1.557654	True	lfc2 and p_value
1	LOC729737	122.155762	1.342039	0.716822	1.872207	0.061178	0.309724	1.213405	False	non-sig
2	TGIF1	1400.037490	-0.099168	0.142399	-0.696411	0.486171	0.796121	0.313211	False	non-sig
3	PRDX6	4794.111981	-0.008120	0.200802	-0.040440	0.967742	0.991057	0.014240	False	non-sig
4	CIC	1581.916300	0.053769	0.177791	0.302430	0.762324	0.925608	0.117860	False	non-sig
...	...	...	...	...	...	...	...	...	...	...
19202	PAK1	2658.104961	-0.314881	0.129934	-2.423387	0.015377	0.143495	1.813142	False	p_value
19203	PRKD3	722.336078	0.175513	0.290260	0.604675	0.545395	0.827693	0.263289	False	non-sig
19204	MLC1	10.608723	-0.444787	0.810487	-0.548790	0.583150	0.846594	0.234220	False	non-sig
19205	ZBTB41	508.407691	-0.547094	0.350267	-1.561933	0.118304	0.427640	0.927002	False	non-sig
19206	TMEM181	1506.912048	-0.395167	0.160578	-2.460906	0.013859	0.135332	1.858278	False	p_value

19207 rows × 10 columns