.. strprofiler documentation master file, created by
sphinx-quickstart on Fri Sep 23 14:58:31 2022.
You can adapt this file completely to your liking, but it should at least
contain the root `toctree` directive.
STRprofiler
===========
.. toctree::
:maxdepth: 2
:caption: Contents:
.. image:: https://zenodo.org/badge/523477912.svg
:target: https://zenodo.org/badge/latestdoi/523477912
**STRprofiler** is a python package, CLI tool, and `Shiny application `__ to compare short tandem repeat (STR) profiles.
In particular, it is designed to aid research labs in comparing models (e.g. cell lines or xenografts) generated from primary tissue samples to ensure authenticity.
It includes basic checks for sample mixing and contamination.
**STRprofiler is intended only for research purposes.**
For each STR profile provided, **STRprofiler** will generate a sample-specific report that includes the following similarity scores as compared to every other profile:
`Tanabe, AKA the Sørenson-Dice coefficient `_:
.. math::
score = \frac{2 * no.shared.alleles}{no.query.alleles + no.reference.alleles}
`Masters (vs. query) `_:
.. math::
score = \frac{no.shared.alleles}{no.query.alleles}
`Masters (vs. reference) `_:
.. math::
score = \frac{no.shared.alleles}{no.reference.alleles}
Amelogenin is not included in the score computation by default but can be included by passing the `--score_amel` flag.
Installation
============
**STRprofiler** is available on PyPi and can be installed with ``pip``::
pip install strprofiler
Usage
=====
.. click:: strprofiler.cli:cli
:prog: strprofiler
:nested: full
Querying CLASTR
===============
**STRprofiler** can also be used to directly query CLASTR via their API.
This can be done from within the Shiny application or from the command line via the ``strprofiler clastr`` subcommand or using the ``clastr_query`` function directly.
Input Files(s)
~~~~~~~~~~~~~~
An example `input file `__ and `reference database `__ are available on GitHub.
**STRprofiler** can take either a single STR file or multiple STR files as input.
These files can be csv, tsv, tab-separated text, or xlsx (first sheet used) files. The STR file(s) should be in either 'wide' or 'long' format.
The long format expects all columns to map to the markers except for the designated sample name column with each row reflecting a different profile, e.g.:
+--------+---------+---------+---------+--------+---------+--------+
| Sample | D1S1656 | DYS391 | D3S1358 | D2S441 | D16S539 | D5S818 |
+========+=========+=========+=========+========+=========+========+
| Line1 | 12,14 | 12 | 13 | 12,14 | 17.3 | 16,17 |
+--------+---------+---------+---------+--------+---------+--------+
| Line2 | 12,14 | 11.3,12 | 13,15 | 12,14 | 17.3 | 16,17 |
+--------+---------+---------+---------+--------+---------+--------+
| ... | | | | | | |
+--------+---------+---------+---------+--------+---------+--------+
The wide format expects a line for each marker for each sample, e.g.:
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample Name | Marker | Allele 1 | Size 1 | Height 1 | Allele 2 | Size 2 | Height 2 | Allele 3 |
+==============+===========+=============+=========+=============+=============+=========+=============+=============+
| Sample1 | DYS391 | | | | | | | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample1 | D3S1358 | 16 | 128.29 | 8268 | 18 | 136.84 | 5467 | 16 |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample1 | D16S539 | 12 | 110.7 | 9660 | 13 | 115.17 | 5215 | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample1 | Penta D | 9 | 415.04 | 5099 | 13 | 435.88 | 9426 | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample1 | D22S1045 | 15 | 455.95 | 13504 | 17 | 462.06 | 6186 | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample1 | Penta E | 11 | 397.7 | 7420 | 14 | 412.02 | 5986 | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample1 | D18S51 | 12 | 153.72 | 9134 | 16 | 170.48 | 10501 | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample1 | D2S1338 | 20 | 263.91 | 3209 | 21 | 267.97 | 3834 | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample1 | TH01 | 7 | 85.33 | 8305 | 9.3 | 97.43 | 7853 | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample1 | D7S820 | 10 | 292.51 | 12340 | 14 | 308.71 | 11784 | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample1 | D12S391 | 15 | 141.53 | 12870 | 18.3 | 157.12 | 13731 | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample1 | AMEL | X | 81.97 | 16696 | | | | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample1 | D10S1248 | 16 | 283.82 | 8469 | | | | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample1 | D13S317 | 12 | 328.21 | 7079 | | | | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample1 | D21S11 | 32.2 | 239.67 | 19231 | | | | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample1 | TPOX | 11 | 424.02 | 12239 | | | | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample1 | D19S433 | 14 | 228.37 | 14273 | | | | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample1 | FGA | 23 | 302.23 | 14599 | | | | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample2 | D16S539 | 9 | 97.59 | 9286 | 11 | 106.43 | 8592 | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample2 | TH01 | 9.3 | 97.45 | 5920 | | | | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample2 | D8S1179 | 13 | 101.1 | 26414 | | | | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample2 | AMEL | X | 82.1 | 7476 | Y | 88.34 | 8029 | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample2 | D3S1358 | 14 | 119.87 | 10146 | 15 | 124.14 | 10160 | 19 |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample2 | D18S51 | 12 | 153.8 | 9316 | 18 | 178.79 | 9182 | 19 |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample2 | Penta D | 10 | 420.13 | 7693 | 11 | 425.25 | 7945 | 12 |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample2 | vWA | 17 | 156.9 | 7953 | 18 | 160.86 | 8230 | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample2 | TPOX | 9 | 416 | 6596 | 11 | 424.02 | 5304 | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample2 | D12S391 | 21 | 166.75 | 13481 | 22 | 170.9 | 14232 | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample2 | D22S1045 | 15 | 455.95 | 14310 | 17 | 462.06 | 10898 | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample2 | D2S441 | 14 | 236.24 | 18628 | | | | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample2 | DYS391 | 10 | 468.83 | 6722 | | | | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
| Sample2 | FGA | 21 | 294.67 | 11941 | | | | |
+--------------+-----------+-------------+---------+-------------+-------------+---------+-------------+-------------+
In this format, the ``marker_col`` must be specified.
Only columns beginning with "Allele" will be used to parse the alleles for each sample/marker.
Any other size or height columns will be ignored.
Output Files
~~~~~~~~~~~~
**STRprofiler** generates two types of output files.
The first is a summary file, which contains the top hits for each sample above the specified scoring thresholds.
This file provides a useful overview in addition to a flag to identify samples with potential mixing for closer inspection.
In the output directory, this file will be named `full_summary.strprofiler.YYYYMMDD.HH_MM_SS.csv` where the date and time are the time the program was run.
In addition to the marker columns, the summary file contains the following columns:
+---------------------------+----------------------------------------------------------------------------+
| **Column Name** | **Description** |
+===========================+============================================================================+
| **mixed** | Flag to indicate sample mixing. |
+---------------------------+----------------------------------------------------------------------------+
| **top_hit** | Name and Tanabe score of top match. |
+---------------------------+----------------------------------------------------------------------------+
| **next_best** | Name and Tanabe score of next best match. |
+---------------------------+----------------------------------------------------------------------------+
| **tanabe_matches** | Name and Tanabe score of matches above scoring threshold. |
+---------------------------+----------------------------------------------------------------------------+
| **masters_query_matches** | Name and Masters (vs. query) score of matches above scoring threshold. |
+---------------------------+----------------------------------------------------------------------------+
| **masters_ref_matches** | Name and Masters (vs. reference) score of matches above scoring threshold. |
+---------------------------+----------------------------------------------------------------------------+
The second is a sample-specific comparison file, which contains the results of the comparison between the query sample and all other provided samples.
These files are generated for each STR profile provided in the input file(s) and named after the query sample in question.
For example, if the input file contains a sample named `Sample1`, the output file will be named `Sample1.strprofiler.YYYYMMDD.HH_MM_SS.csv`.
In addition to the marker columns, this output contains the following columns:
+-------------------------+--------------------------------------------------------------+
| **Column Name** | **Description** |
+=========================+==============================================================+
| **mixed** | Flag to indicate sample mixing. |
+-------------------------+--------------------------------------------------------------+
| **query_sample** | Flag to indicate query sample. |
+-------------------------+--------------------------------------------------------------+
| **n_shared_markers** | Number of shared markers between query and reference sample. |
+-------------------------+--------------------------------------------------------------+
| **n_shared_alleles** | Number of shared alleles between query and reference sample. |
+-------------------------+--------------------------------------------------------------+
| **n_query_alleles** | Total number of alleles in query sample. |
+-------------------------+--------------------------------------------------------------+
| **n_reference_alleles** | Total number of alleles in reference sample. |
+-------------------------+--------------------------------------------------------------+
| **tanabe_score** | Tanabe similarity score. |
+-------------------------+--------------------------------------------------------------+
| **masters_query_score** | Masters (vs query) similarity score. |
+-------------------------+--------------------------------------------------------------+
| **masters_ref_score** | Masters (vs reference) similarity score. |
+-------------------------+--------------------------------------------------------------+
Database Comparison
~~~~~~~~~~~~~~~~~~~
**STRprofiler** can be also used to compare batches of samples against a larger database of samples.
.. code:: bash
strprofiler compare -db ExampleSTR_database.csv -o ./strprofiler_output STR1.xlsx
In this mode, inputs are compared against the database samples only, and not among themselves.
Outputs will be as described above for sample input(s).
Database Format
^^^^^^^^^^^^^^^
The database should be formatted as a samples by markers matrix and saved as a csv file, e.g:
+-----------+------------+--------+---------+---------+--------+---------+---------+---------+---------+
| Sample | Amelogenin | CSF1PO | D13S317 | D16S539 | D18S51 | D19S433 | D21S11 | D2S1338 | D3S1358 |
+===========+============+========+=========+=========+========+=========+=========+=========+=========+
| sample1 | X,Y | 12 | 8 | 13 | 14 | 14 | 31,31.2 | 17,19 | 15 |
+-----------+------------+--------+---------+---------+--------+---------+---------+---------+---------+
| sample2 | X | 10 | 9 | 13 | 16 | 12,14 | 29 | 20,23 | 15,16 |
+-----------+------------+--------+---------+---------+--------+---------+---------+---------+---------+
Optionally, one may provide two metadata columns - "Center" and "Passage", which will be recognized as non-marker columns.
The ``STRprofiler`` App
=======================
New in v0.2.0 is ``strprofiler app``, a subcommand that launches a Shiny application that allows for user queries against an uploaded or pre-defined database (provided with the `-db` parameter) of STR profiles.
This application can provide a convenient portal to a group's STR database and can be hosted on standard Shiny servers, Posit Connect instances, or ShinyApps.io.
An example of the application can be seen `here `__.
Deploying an ``STRprofiler`` App
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Building an app for deployment to any of the above options is simple.
First, make your app.py file:
.. code:: python
from strprofiler.shiny_app.shiny_app import create_app
database = "./tester_db.csv"
app = create_app(db=database)
If no database is provided, an example database included with the package will be used.
The database file should be a csv file with the same format as described above.
Then create a requirements.txt file in the same directory with `strprofiler` listed:
.. code:: bash
strprofiler>=0.4.0
This app can then be deployed to any of the above endpoints as `one would with any other Shiny app `__.
.. code:: bash
rsconnect deploy shiny -n your_server -t STRprofiler .
Alternatively, one could export it as a shinylive app and host it on Github pages or similar.
Other Functions
===============
.. automodule:: strprofiler.utils
:members:
Contributing
============
You can contribute by creating `issues `_ to highlight bugs and make suggestions for additional features. `Pull requests `_ are also very welcome.
License
=======
**STRprofiler** is released on the MIT license. You are free to use, modify, or redistribute it in almost any way, provided you state changes to the code, disclose the source, and use the same license.
It is released with zero warranty for any purpose and the authors retain no liability for its use.
`Read the full license `_ for additional details.
Reference
=========
If you use **STRprofiler** in your research, please cite the following:
Jared Andrews, Mike Lloyd, & Sam Culley. (2024). j-andrews7/strprofiler: v0.4.0 (v0.4.0). Zenodo. https://doi.org/10.5281/zenodo.7348386
Indices and tables
==================
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`