Sample Pool Aliquot Size Calculator
This package can be used to quickly calculate the ratio of 1 unit volume one may need to use so that all aliquots contain the same amount of proteomics content
Dependencies
pandas = "^1.4.3"
Usage
import pandas as pd
from sample_pool.experiment import Experiment
# Read tabulated text file containing the data
path = r".\RN_220625_Hippo-TiO2_15TMT_Minipool_PSMs.txt"
df = pd.read_csv(path, sep="\t")
# Create a variable with list of columns containing sample data
samples = [
"Abundance: 126",
"Abundance: 127N",
"Abundance: 127C",
"Abundance: 128N",
"Abundance: 128C",
"Abundance: 129N",
"Abundance: 129C",
"Abundance: 130N",
"Abundance: 130C",
"Abundance: 131N",
"Abundance: 131C",
"Abundance: 132N",
"Abundance: 132C",
"Abundance: 133N",
"Abundance: 133C"
]
# Create Experiment object with the dataframe and sample list as parameters
exp = Experiment(df, samples)
# Get aliquot size ratio as a dictionary with key being sample name and value being volume ratio
size = exp.get_aliquot_size(minimum_good_samples=10)
# By default get_aliquot_size would use the sample with the lowest normalized sum intensity as the base for ratio calculation. To specify the sample, you can use based_on_sample parameter.
size = exp.get_aliquot_size(based_on_sample="Abundance: 127C", minimum_good_samples=10)
print(size)
Metadata
Release files for sample-pool 1.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| sample_pool-1.0.0.tar.gz | 3.2 kB | Without provenance | Details for sample_pool-1.0.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| sample_pool-1.0.0-py3-none-any.whl | Python 3 | none | any | Details for sample_pool-1.0.0-py3-none-any.whl |
Total release size: 6.4 kB
Release files / sample_pool-1.0.0.tar.gz
| Download URL | sample_pool-1.0.0.tar.gz |
|---|---|
| Size | 3.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
31acaddc97dfd9e48f0a3631d87f05fc2d8d90c2af14fc667d577339116ca844
|
|
BLAKE2b-256 checksum How to use checksums |
00b658c45e0782e82526118d12f1edcf7a602a85697622417e480b6db7f1e9c7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.1.13 CPython/3.9.10 Windows/10
|
Release files / sample_pool-1.0.0-py3-none-any.whl
| Download URL | sample_pool-1.0.0-py3-none-any.whl |
|---|---|
| Size | 3.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
3e9a72465c4781d219597124279e8793882e670b8b1440c62bb733869f040955
|
|
BLAKE2b-256 checksum How to use checksums |
b671be852d5b2d90a0b5a8ddb43777d482d91b6f34677d0bd462aca204c30849
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.1.13 CPython/3.9.10 Windows/10
|
Security for sample-pool 1.0.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.