Details
-
Type:
Task
-
Status: Closed (View Workflow)
-
Priority:
Major
-
Resolution: Done
-
Affects Version/s: None
-
Fix Version/s: None
-
Labels:None
-
Story Points:2
-
Epic Link:
-
Sprint:Fall 2, Fall 3, Fall 4
Description
GOAL: To attempt to implement one of the various K-mean clustering strategies on Kelsey's Pollinated dataset.
The reason: Her committee asked. This is to mostly silence them. Or maybe we will get some really cool insight!
The input will be the deseq2 normalized data (not DSeseq results). No idea what tools we mgiht try yet. This ticket is to come up with a plan of attack. New tickets needed for actual implementation.
Attachments
Activity
| Field | Original Value | New Value |
|---|---|---|
| Epic Link | IGBF-2993 [ 21429 ] |
| Assignee | Ann Loraine [ aloraine ] | Robert Reid [ robertreid ] |
| Status | To-Do [ 10305 ] | In Progress [ 3 ] |
| Sprint | Fall 2 [ 225 ] | Fall 2, Fall 3 [ 225, 226 ] |
| Rank | Ranked higher |
| Status | In Progress [ 3 ] | To-Do [ 10305 ] |
| Status | To-Do [ 10305 ] | In Progress [ 3 ] |
| Assignee | Robert Reid [ robertreid ] | Brandon Bendickson [ bbendick ] |
| Sprint | Fall 2, Fall 3 [ 225, 226 ] | Fall 2, Fall 3, Fall 4 [ 225, 226, 227 ] |
| Rank | Ranked higher |
| Status | In Progress [ 3 ] | Needs 1st Level Review [ 10005 ] |
| Status | Needs 1st Level Review [ 10005 ] | First Level Review in Progress [ 10301 ] |
| Status | First Level Review in Progress [ 10301 ] | Ready for Pull Request [ 10304 ] |
| Status | Ready for Pull Request [ 10304 ] | Pull Request Submitted [ 10101 ] |
| Status | Pull Request Submitted [ 10101 ] | Reviewing Pull Request [ 10303 ] |
| Status | Reviewing Pull Request [ 10303 ] | Merged Needs Testing [ 10002 ] |
| Status | Merged Needs Testing [ 10002 ] | Post-merge Testing In Progress [ 10003 ] |
| Resolution | Done [ 10000 ] | |
| Status | Post-merge Testing In Progress [ 10003 ] | Closed [ 6 ] |
Several literature sources tell us that K-means is not effective for timecourse/multisample rna seq data, but to use model based clustering instead. Shifting to a tool called mClust in R