I feel confident enough to declare sector 4 complete!
I changed my approach midway through this sector and moved to identifying photoreceptors by cluster (L1+R1-8) and found it a lot easier to follow in this sector. Also noticing a few distinct shape patterns in R1-6 that may help in further narrowing these types down, though I haven’t taken any deep dive into those patterns.
Sheet is updated and here’s a handy link here: FlyWire
(Going to take a small break out of these sectors to go back over my right lobe T4-T5 cells/cell farms but from here on out I am going to try to alternate work on that and photoreceptors since there’s many to go!)
Congrats on finishing Sector 4 @AzureJay! I’m glad you found the L1+R1-8 method a little easier. I also prefer to use the L1 cell as a major touchstone for finding certain cell types in a cluster/ommatidium.
PS. Let us know if you have any questions about your T4 or T5 cells – happy to help
another 100 clusters of retinal cells from the right lobe done, this time in the area not affected by the rift, with my 200 clusters i have a band that goes almost from one end of the lobe to the other.
As part of a joint effort from Flyers, Princeton lab members and researchers, the Photoreceptor Zone Quest has been completed!
Together, we proofread a total of 5k+ retinula cells in the right optic lobe using a variety of mapping processes (ie. spatial zones, common synaptic partners) to ensure full coverage. Thank you for your contribution and efforts to this Quest. We are now casting a wider net and focusing on tagging cells in the visual system. Happy Flying!
PS. If you’d like to attempt loading all 5k+ photoreceptors, here’s the link: neuroglancer (warning: this link takes really long time to see loading, be patient )
after looking at the Dm8 cells classified by kk in the cell farms there is a lot of cells not marked as identified and i guess this might be the case in the other cell farms also. i am thinking the fastest way to get many cells is too look at the cells farm and identify the cells that did not get identified the first round
we should probably also have a system so not everyone is working on tagging the same type
As for the Dm8, I wasn’t 100% sure about all the identifications, so I didn’t label them (hence the purple field in the “Status” column). If the field is green, that means, that I (or someone else) have already labeled (almost) all cells.
ah okay, i am seeing it now, did have very little time too look at it this morning so forgot too look at the colour in the sheet.
i was just wondering on the difference betwheen the tagging dashboard and cell farms on a few but a big part of the explanation could be there then.
Another sector of 100 R clusters done, this one did go really fast since most of the cells are completed and a lot of them already identified. But still 290 cells was missing identification in this batch.