diff --git a/README.md b/README.md
index 7a91dfe..9770deb 100644
--- a/README.md
+++ b/README.md
@@ -14,18 +14,20 @@ A collection of python scripts to create high time resolution light curves from
* If using CASA v5 and above, use instructions [here](http://docs.astropy.org/en/stable/install.html)
e.g., `casa --no-logger --log2term -c "from setuptools.command import easy_install; easy_install.main(['--user', 'pip'])"`
`casa --no-logger --log2term -c "import pip; pip.main(['install', 'astropy', '--user']); pip.main(['install', 'astroML', '--user']); pip.main(['install', 'jdcal', '--user'])"`
+* **analysisUtils** (get it [here](https://casaguides.nrao.edu/index.php?title=Analysis_Utilities))
* (*optional*) For UV plane fitting, **uvmultifit** (get it [here](http://nordic-alma.se/support/software-tools))
* (*optional*) To use object detection,
- * **analysisUtils** (get it [here](https://casaguides.nrao.edu/index.php?title=Analysis_Utilities))
* **aegean** (see [here](https://github.com/PaulHancock/Aegean))
To install,
`casa --no-logger --log2term -c "import pip; pip.main(['install', 'git+https://github.com/PaulHancock/Aegean.git', '--user'])"`
## If you want to use these scripts on your own machine, you only need,
1. **casa_timing_script.py**: intended to be run within CASA. This is the script that does all the hard work.
+ * Please create a split MS, with only the target present, for these scripts.
* All parameters need to be carefully considered and changed for each new data set.
* If you have a complicated field with other sources it is recommended that you use your own mask file (with clean boxes around bright sources; mask_option='file') for cleaning, or run object detection, which will create a mask file with a boxed region around each detected source (mask_option='aegean').
* If you are using an outlier field file, please follow the example template in example_outlier_file.txt.
+ * If you are doing uv fitting, please follow the example inital paramters template in uv_init_example.txt.
* Included in casa_timing_script.py is the option to run basic variability analysis:
* Calculate weighted mean and do a chi^2 with a constant flux model,
* Calculate excess variance,