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CytoSig-0.0.2
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مشاهده بیشترتوضیحات
Prediction model for cytokine signaling activity
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | CytoSig-0.0.2 |
| نام | CytoSig |
| نسخه کتابخانه | 0.0.2 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Peng Jiang |
| ایمیل نویسنده | peng.jiang@nih.gov |
| آدرس صفحه اصلی | https://github.com/data2intelligence/CytoSig |
| آدرس اینترنتی | https://pypi.org/project/CytoSig/ |
| مجوز | - |
CytoSig prediction model of cytokine signaling activity
**Prerequisite**:
1, ridge_significance: https://github.com/data2intelligence/ridge_significance
Please read its README.md and run test to make sure the successful installation.
2, pandas >= 1.1.4: You may install anaconda (https://www.anaconda.com) to include all required python packages.
3, xlsxwriter >= 1.3.7: pip install --upgrade xlsxwriter
**Install**:
python setup.py install
**Test**:
python -m unittest tests.prediction
Please see **tests/prediction.py** for examples of two usages explained below.
**Usage 1, through command line**:
CytoSig_run.py -i input_profile -o output_prefix -r random_count -a penalty_alpha -e generate_excel -s expand_signature
1, input_profile: input matrix of biological profiles. Each column is a biological condition, and each row should be a human gene symbol. Please see "tests/GSE147507.diff.gz" as an example.
The expression values, from either RNASeq or MicroArray, should be transformed by log2(x+1). x could be FPKM, RPKM, or TPM for RNASeq. For single-cell RNASeq data, we used log2(TPM/10 + 1). We also recommend quantile-normalization across conditions. Some software package, such as RMA or DESeq, will automatically include all normalizations. We recommend input differential profiles between the two conditions. If data is from a sample collection without pairs, please mean-centralize the value of each gene across all samples.
2, output_prefix: prefix of output files. Each column is a biological condition, and each row is a cytokine name
output_prefix.Coef: regression coefficients
output_prefix.StdErr: standard error
output_prefix.Zscore: Coef/StdErr
output_prefix.Pvalue: two-sided test p-value of Zscore, from permutation test if random_count > 0 or student t-test if random_count = 0
output_prefix.xlsx: only exist if generate_excel = 1. A excel summary of results, with each input condition as one tab
3, random_count: number of randomizations in the permutation test, with a default value 1000. If value is 0, the program will use student t-test.
4, penalty_alpha: penalty weight in the ridge regression, with a default value 10000.
5, generate_excel: whether generate excel output. The value could be 1 (Yes) or 0 (No) with a default value 0. This option is only effective when the input condition count is less than 50.
6, expand_signature: whether use an expanded signature of cytokine response. Our initial cytokine response signature included 43 cytokines with high confidence data. However, we can also set a less stringent filter to include 51 cytokines.
Example:
In the directory of README.md, please type: CytoSig_run.py -i tests/GSE147507.diff.gz -o tests/output_test -e 1
Then, open "tests/output_test.xlsx" to view results
**Usage 2, through Python function inside your customized code**:
Input:
Y: the expression matrix of your samples in pandas data frame. Each column name is a sample ID. Each row name is a human gene symbol.
Output: four pandas data frames
beta: regression coefficients
std: standard errors of coefficients
zscore: beta/std
pvalue: statistical significance
Then, use the following code snippet in your program:
import os, sys, pandas, CytoSig
signature = os.path.join(sys.prefix, 'bin', 'signature.centroid') # load cytokine response signature installed in your python system path
signature = pandas.read_csv(signature, sep='\t', index_col=0)
beta, std, zscore, pvalue = CytoSig.ridge_significance_test(signature, Y, alpha=1E4, alternative="two-sided", nrand=1000, cnt_thres=10, flag_normalize=True, verbose = True)
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.6 | Python |
نحوه نصب
نصب پکیج whl CytoSig-0.0.2:
pip install CytoSig-0.0.2.whl
نصب پکیج tar.gz CytoSig-0.0.2:
pip install CytoSig-0.0.2.tar.gz