Details
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Type:
New Feature
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Status: Closed (View Workflow)
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Priority:
Major
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Resolution: Done
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Affects Version/s: None
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Fix Version/s: None
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Labels:None
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Story Points:4
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Epic Link:
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Sprint:Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Summer 2019 Sprint 10, Summer 2019 Sprint 11, Summer 2019 Sprint 12, Fall 2019 Sprint 1, Fall 2019 Sprint 2, Fall 2019 Sprint 3
Description
A potential App developer asks:
"can I extract from IGB values for selected/all loaded lines for selected genomic region? For example, I have two tracks for ChIP-seq against two different transcription factors and I want to know what is their average score for selected region e.q. 1kb or 10kb. Can I have also information about which genes (mRNA) are present in this region or values for any other line?"
Investigate:
- How does an App find out what tracks are loaded (or selected) in IGB?
- How does an App access the loaded data for a region?
Tip:
- Look at how track filters and operators work.
*EDIT*: Instead of documenting, let's create a demo App that shows how these things can be done. For spec, see June 2019 comments from Dr. Loraine.
Attachments
Issue Links
Activity
| Assignee | Ann Loraine [ aloraine ] |
| Rank | Ranked higher |
| Rank | Ranked higher |
| Description |
An App developer asks:
"can I extract from IGB values for selected/all loaded lines for selected genomic region? For example, I have two tracks for ChIP-seq against two different transcription factors and I want to know what is their average score for selected region e.q. 1kb or 10kb. Can I have also information about which genes (mRNA) are present in this region or values for any other line?" Investigate how this could be done and add comments here: * How does an App find out what tracks are loaded (or selected) in IGB? * How does an App access the loaded data for a region? Tip: * Look at how track filters and operators work. |
An App developer asks:
"can I extract from IGB values for selected/all loaded lines for selected genomic region? For example, I have two tracks for ChIP-seq against two different transcription factors and I want to know what is their average score for selected region e.q. 1kb or 10kb. Can I have also information about which genes (mRNA) are present in this region or values for any other line?" Investigate how this could be done and add comments here: * How does an App find out what tracks are loaded (or selected) in IGB? * How does an App access the loaded data for a region? Tip: * Look at how track filters and operators work. * Look at IGB App code |
| Assignee | Ivory Blakley [ ieclabau ] |
| Rank | Ranked higher |
| Status | Open [ 1 ] | In Progress [ 3 ] |
| Status | In Progress [ 3 ] | Open [ 1 ] |
| Status | Open [ 1 ] | In Progress [ 3 ] |
| Rank | Ranked higher |
| Sprint | Summer 2018 Part 2 [ 49 ] | Summer 2018 Part 2, Summer 2018 Part 3 [ 49, 50 ] |
| Rank | Ranked higher |
| Assignee | Ivory Blakley [ ieclabau ] | Ann Loraine [ aloraine ] |
| Status | In Progress [ 3 ] | Open [ 1 ] |
| Rank | Ranked higher |
| Sprint | Summer 2018 Part 2, Summer 2018 Part 3 [ 49, 50 ] | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1 [ 49, 50, 51 ] |
| Rank | Ranked lower |
| Story Points | 1 | 2 |
| Rank | Ranked higher |
| Sprint | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1 [ 49, 50, 51 ] | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Fall 2018 Sprint 2 [ 49, 50, 51, 52 ] |
| Rank | Ranked lower |
| Sprint | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Fall 2018 Sprint 2 [ 49, 50, 51, 52 ] | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1 [ 49, 50, 51 ] |
| Rank | Ranked higher |
| Fix Version/s | 9.0.2 Minor Release [ 10600 ] |
| Assignee | Ann Loraine [ aloraine ] |
| Rank | Ranked higher |
| Summary | Document how Apps get access to track data | Document how Apps can get access to track data |
| Rank | Ranked higher |
| Epic Link | IGBF-1531 [ 17617 ] |
| Sprint | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1 [ 49, 50, 51 ] | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Spring 2019 Sprint 7 [ 49, 50, 51, 66 ] |
| Assignee | Ann Loraine [ aloraine ] |
| Sprint | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Spring 2019 Sprint 7 [ 49, 50, 51, 66 ] | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Summer 2019 Sprint 8 [ 49, 50, 51, 67 ] |
| Rank | Ranked lower |
| Sprint | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Summer 2019 Sprint 8 [ 49, 50, 51, 67 ] | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1 [ 49, 50, 51 ] |
| Rank | Ranked higher |
| Rank | Ranked higher |
| Assignee | Ann Loraine [ aloraine ] |
| Sprint | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1 [ 49, 50, 51 ] | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Summer 2019 Sprint 11 [ 49, 50, 51, 70 ] |
| Rank | Ranked higher |
| Sprint | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Summer 2019 Sprint 11 [ 49, 50, 51, 70 ] | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Summer 2019 Sprint 10 [ 49, 50, 51, 69 ] |
| Rank | Ranked higher |
| Summary | Document how Apps can get access to track data | Demonstrate how Apps can get access to track data |
| Issue Type | Bug [ 1 ] | New Feature [ 2 ] |
| Story Points | 2 | 3 |
| Description |
An App developer asks:
"can I extract from IGB values for selected/all loaded lines for selected genomic region? For example, I have two tracks for ChIP-seq against two different transcription factors and I want to know what is their average score for selected region e.q. 1kb or 10kb. Can I have also information about which genes (mRNA) are present in this region or values for any other line?" Investigate how this could be done and add comments here: * How does an App find out what tracks are loaded (or selected) in IGB? * How does an App access the loaded data for a region? Tip: * Look at how track filters and operators work. * Look at IGB App code |
A potential App developer asks:
"can I extract from IGB values for selected/all loaded lines for selected genomic region? For example, I have two tracks for ChIP-seq against two different transcription factors and I want to know what is their average score for selected region e.q. 1kb or 10kb. Can I have also information about which genes (mRNA) are present in this region or values for any other line?" Investigate: * How does an App find out what tracks are loaded (or selected) in IGB? * How does an App access the loaded data for a region? Tip: * Look at how track filters and operators work. |
| Description |
A potential App developer asks:
"can I extract from IGB values for selected/all loaded lines for selected genomic region? For example, I have two tracks for ChIP-seq against two different transcription factors and I want to know what is their average score for selected region e.q. 1kb or 10kb. Can I have also information about which genes (mRNA) are present in this region or values for any other line?" Investigate: * How does an App find out what tracks are loaded (or selected) in IGB? * How does an App access the loaded data for a region? Tip: * Look at how track filters and operators work. |
A potential App developer asks:
"can I extract from IGB values for selected/all loaded lines for selected genomic region? For example, I have two tracks for ChIP-seq against two different transcription factors and I want to know what is their average score for selected region e.q. 1kb or 10kb. Can I have also information about which genes (mRNA) are present in this region or values for any other line?" Investigate: * How does an App find out what tracks are loaded (or selected) in IGB? * How does an App access the loaded data for a region? Tip: * Look at how track filters and operators work. **EDIT**: Instead of documenting, let's create a demo App that shows how these things can be done. For spec, see June 2019 comments from Dr. Loraine. |
| Story Points | 3 | 4 |
| Summary | Demonstrate how Apps can get access to track data | Make a new IGB "demo" App that shows how Apps can get access to track data |
| Assignee | Shamika Gajanan Kulkarni [ shamika ] |
| Status | Open [ 1 ] | In Progress [ 3 ] |
| Sprint | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Summer 2019 Sprint 10 [ 49, 50, 51, 69 ] | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Summer 2019 Sprint 10, Summer 2019 Sprint 11 [ 49, 50, 51, 69, 70 ] |
| Rank | Ranked higher |
| Status | In Progress [ 3 ] | Open [ 1 ] |
| Status | Open [ 1 ] | In Progress [ 3 ] |
| Sprint | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Summer 2019 Sprint 10, Summer 2019 Sprint 11 [ 49, 50, 51, 69, 70 ] | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Summer 2019 Sprint 10, Summer 2019 Sprint 11, Summer 2019 Sprint 12 [ 49, 50, 51, 69, 70, 71 ] |
| Rank | Ranked higher |
| Status | In Progress [ 3 ] | Open [ 1 ] |
| Status | Open [ 1 ] | In Progress [ 3 ] |
| Status | In Progress [ 3 ] | Needs 1st Level Review [ 10005 ] |
| Assignee | Shamika Gajanan Kulkarni [ shamika ] |
| Sprint | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Summer 2019 Sprint 10, Summer 2019 Sprint 11, Summer 2019 Sprint 12 [ 49, 50, 51, 69, 70, 71 ] | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Summer 2019 Sprint 10, Summer 2019 Sprint 11, Summer 2019 Sprint 12, Fall 2019 Sprint 1 [ 49, 50, 51, 69, 70, 71, 72 ] |
| Rank | Ranked higher |
| Workflow | Loraine Lab Workflow [ 18047 ] | Fall 2019 Workflow Update [ 19047 ] |
| Sprint | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Summer 2019 Sprint 10, Summer 2019 Sprint 11, Summer 2019 Sprint 12, Fall 2019 Sprint 1 [ 49, 50, 51, 69, 70, 71, 72 ] | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Summer 2019 Sprint 10, Summer 2019 Sprint 11, Summer 2019 Sprint 12, Fall 2019 Sprint 1, Fall 2019 Sprint 2 [ 49, 50, 51, 69, 70, 71, 72, 73 ] |
| Rank | Ranked higher |
| Rank | Ranked lower |
| Assignee | Prutha Kulkarni [ prutha ] |
| Status | Needs 1st Level Review [ 10005 ] | First Level Review in Progress [ 10301 ] |
| Status | First Level Review in Progress [ 10301 ] | To-Do [ 10305 ] |
| Assignee | Prutha Kulkarni [ prutha ] | Shamika Gajanan Kulkarni [ shamika ] |
| Status | To-Do [ 10305 ] | In Progress [ 3 ] |
| Status | In Progress [ 3 ] | Needs 1st Level Review [ 10005 ] |
| Assignee | Shamika Gajanan Kulkarni [ shamika ] | Prutha Kulkarni [ prutha ] |
| Status | Needs 1st Level Review [ 10005 ] | First Level Review in Progress [ 10301 ] |
| Assignee | Prutha Kulkarni [ prutha ] | Shamika Gajanan Kulkarni [ shamika ] |
| Status | First Level Review in Progress [ 10301 ] | Ready for Pull Request [ 10304 ] |
| Sprint | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Summer 2019 Sprint 10, Summer 2019 Sprint 11, Summer 2019 Sprint 12, Fall 2019 Sprint 1, Fall 2019 Sprint 2 [ 49, 50, 51, 69, 70, 71, 72, 73 ] | Summer 2018 Part 2, Summer 2018 Part 3, Fall 2018 1, Summer 2019 Sprint 10, Summer 2019 Sprint 11, Summer 2019 Sprint 12, Fall 2019 Sprint 1, Fall 2019 Sprint 2, Fall 2019 Sprint 4 [ 49, 50, 51, 69, 70, 71, 72, 73, 74 ] |
| Rank | Ranked higher |
| Status | Ready for Pull Request [ 10304 ] | Pull Request Submitted [ 10101 ] |
| Assignee | Shamika Gajanan Kulkarni [ shamika ] | Ann Loraine [ aloraine ] |
| 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 ] |
| Status | Post-merge Testing In Progress [ 10003 ] | Closed [ 6 ] |
| Assignee | Ann Loraine [ aloraine ] | Shamika Gajanan Kulkarni [ shamika ] |
| Resolution | Done [ 10000 ] |
| Workflow | Fall 2019 Workflow Update [ 19047 ] | Revised Fall 2019 Workflow Update [ 22041 ] |
| Assignee | Shamika Gajanan Kulkarni [ shamika ] | Ann Loraine [ aloraine ] |