Update Readme with Citation section

README.md

@@ -6,6 +6,7 @@
 [![Coverage Status](https://codecov.io/gh/cytomining/pycytominer/branch/main/graph/badge.svg)](https://codecov.io/github/cytomining/pycytominer?branch=main)
 [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
 [![RTD](https://readthedocs.org/projects/pycytominer/badge/?version=latest&style=flat)](https://pycytominer.readthedocs.io/)
+[![DOI](https://img.shields.io/badge/DOI-10.48550/arXiv.2311.13417-blue)](https://doi.org/10.48550/arXiv.2311.13417)
 
 Pycytominer is a suite of common functions used to process high dimensional readouts from high-throughput cell experiments.
 The tool is most often used for processing data through the following pipeline:
@@ -110,9 +111,17 @@ And, more specifically than that, image-based profiling readouts from [CellProfi
 
 Therefore, we have included some custom tools in `pycytominer/cyto_utils` that provides other functionality:
 
-- [CellProfiler CSV collation](#CellProfiler-CSV-collation)
-- [Cell locations lookup table generation](#Creating-a-cell-locations-lookup-table)
-- [Generating gct files for Morpheus visualization](#Generating-a-GCT-file-for-morpheus)
+- [Data processing for image-based profiling](#data-processing-for-image-based-profiling)
+  - [Installation](#installation)
+  - [Frameworks](#frameworks)
+  - [API](#api)
+  - [Usage](#usage)
+    - [Pipeline orchestration](#pipeline-orchestration)
+  - [Other functionality](#other-functionality)
+    - [CellProfiler CSV collation](#cellprofiler-csv-collation)
+    - [Creating a cell locations lookup table](#creating-a-cell-locations-lookup-table)
+    - [Generating a GCT file for morpheus](#generating-a-gct-file-for-morpheus)
+  - [Citing pycytominer](#citing-pycytominer)
 
 Note, [`pycytominer.cyto_utils.cells.SingleCells()`](pycytominer/cyto_utils/cells.py) contains code to interact with single-cell SQLite files, which are output from CellProfiler.
 Processing capabilities for SQLite files depends on SQLite file size and your available computational resources (for ex. memory and cores).
@@ -194,3 +203,10 @@ pycytominer.cyto_utils.write_gct(
     output_file=output_file
 )
 ```
+
+## Citing pycytominer
+
+If you have used the `pycytominer` in your work, please consider citing our preprint:
+
+> Erik Serrano, Srinivas Niranj Chandrasekaran, Dave Bunten, Kenneth I. Brewer, Jenna Tomkinson, Roshan Kern, Michael Bornholdt, Stephen Fleming, Ruifan Pei, John Arevalo, Hillary Tsang, Vincent Rubinetti, Callum Tromans-Coia, Tim Becker, Erin Weisbart, Charlotte Bunne, Alexandr A. Kalinin, Rebecca Senft, Stephen J. Taylor, Nasim Jamali, Adeniyi Adeboye, Hamdah Shafqat Abbasi, Allen Goodman, Juan C. Caicedo, Anne E. Carpenter, Beth A. Cimini, Shantanu Singh, Gregory P. Way. (2023): [Reproducible image-based profiling with Pycytominer](https://arxiv.org/abs/2311.13417)
+> DOI: <https://doi.org/10.48550/arXiv.2311.13417>