Comments (6)
from cnnc.
another reminder,
all command lines are just used for demo. If you want to run the whole real data, plz replace "mmukegg_new_new_unique_rand_labelx_num_sy.txt" with "mmukegg_new_new_unique_rand_labelx_num.txt", and replace all "9" with '3057', which is the real number of separations
from cnnc.
@xiaoyeye Thank you for looking into this.
I have another question about line 128 in get_xy_label_data_cnn_combine_from_database.py
128: HT_bulk = (log10(H_bulk / 43261 + 10 ** -4) + 4)/4
I understand that in line 134 you would divide by 43261 since that is the number of cells in sc data, why divide bulk data by 43261 instead of 249?
Thanks,
Aditya
from cnnc.
from cnnc.
And, perhaps the range of [0,1] is not necessary, once all train and test data are uniformly normalized, the network should work well.
from cnnc.
Sure, I'll go ahead and use sample size for normalization.
I was just curious because in order to have a range of (0,1] I thought we should just divide by 249 for bulk data, since dividing the bulk data's histogram values by 43261 would have a range of at most (0,249/43261] which is approximately (0,0.006].
Thank you for taking the time to address my comments.
-Aditya
from cnnc.
Related Issues (20)
- Running predict_no_y.py with bulk data only HOT 3
- Question about data files HOT 1
- Data source of rank_total_gene_rpkm.h5 HOT 5
- Question about mesc_sc_gene_list.txt HOT 1
- unable to achieve the accuracy from paper HOT 5
- Confusion regarding inputs HOT 12
- What's the meaning of "data separation index list" file? HOT 6
- Can’t generate NEPDF data for the example sc-RNA seq data HOT 5
- The labels of result array? HOT 4
- Conda environment HOT 2
- Confusion about how the KEGG edges were filtered HOT 1
- Validation set query HOT 1
- histogram2d output transformation HOT 1
- ChIP-seq peak p-value information
- confusion about the CNNC model
- Troubles when using pretrained KEGG model
- PRE-TRAINED MODELS
- Is CNCC available in R? HOT 1
- train a new model
- Ability to use multiple scRNAseq datasets
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from cnnc.