Commit to Bitbucket:
https://bitbucket.org/hotpollen/time-series/commits/eb84ceac06f5ef1c2e89d7960019d94a3be3c73e

Update:

• [~RobertReid] reviewed the files.

Need to do:

• Change print commands to just include head() of tables.
• Add files to drive for tomato group
  Drive location: https://drive.google.com/drive/folders/1_I6PLSoBg4H3Y1MzY2qhxjk-FBmM4cmQ?usp=share_link
• Update bitbucket with new changes to Rmd file with commit.

Made commit to bitbucket:

• https://bitbucket.org/hotpollen/time-series/commits/cd23c7c2c4688e470925d063a11c0b225800e07c

Includes R markdown, count file, and a final dataframe as a csv file.

EBSeq_tomato.Rmd
mark-timeseries-SL5-salmoncounts.txt
all_data_clusters.csv

Result from today's discussion:

1) Run the clustering algorithm on the following sample groups:

• Heinz stress, MP, 30 min, 60 min, 120 min
• Heinz control, MP, 30 min, 60 min, 120 min
• Tamaulipas stress, MP, 30 min, 60 min, 120 min
• Tamaulipas control, MP, 30 min, 60 min, 120 min
• Nagcarlang stress, MP, 30 min, 60 min, 120 min
• Nagcarlang control, MP, 30 min, 60 min, 120 min

This will create some EBSeq-HMM objects corresponding to clusters, where each cluster has a name like "UP-UP-UP".

2) Next, write out them into one tab-separated file with the following columns:

• cluster name (e.g., UP-UP-UP)
• SL5 gene name
• genotype (e.g., Heinz, Nagcarlang or Tamaulipas)
• temperature (e.g., C.28, S.34)

Update:

• Dr. Reid created a new merged table with results from "seedlingPollen" and "mark-2022-timeseries" in the Charlotte cluster file system.
  File: mark-timeseries-SL5-salmoncounts.txt
• I ran EB-Seq on the merged file and produced cluster path txt files.
• I am still trying to figure our how to create human readable files. I am having difficulty making it a spreadsheet because there would be a different number of rows or columns to each label.
• Currently also trying to make Venn diagrams to compare cluster files.

Next Step: Make directory and share with collaborators.