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epigen
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unsupervised_analysis
A general purpose Snakemake workflow to perform unsupervised analyses (dimensionality reduction & cluster analysis) and visualizations of high-dimensional data.
MIT License
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clustification v1
#54
sreichl
opened
3 months ago
0
Segmentation fault bug with UMAP diagnostic step
#53
JakeLehle
closed
3 months ago
5
Update leiden.yaml
#52
JakeLehle
closed
3 months ago
5
enhance Snakemake report using labels
#51
sreichl
closed
3 months ago
0
provide PCA configurations, eg % of variance to keep, to speed up for large data
#49
sreichl
closed
3 months ago
0
clustification: train/predict on approximated manifold instead of original space
#48
sreichl
opened
4 months ago
0
clustification: implement XGBoost
#47
sreichl
opened
4 months ago
0
make cluster validation using indices optional
#46
sreichl
closed
3 months ago
0
Error plot_dimred_metadata
#45
bednarsky
closed
3 months ago
2
UMAP diagnostics bug - numba intersect1d
#44
bednarsky
closed
3 months ago
4
snakemake找不到srcdir函数
#43
summersohot
closed
4 months ago
5
consider adding CartoGRAPHs for visualization and DataDiVR export for VR based analysis
#42
sreichl
opened
8 months ago
0
diagnostic plot of all aggregated clustering results
#41
sreichl
opened
9 months ago
1
fix job selection for cluster indices without clusterings
#40
sreichl
closed
9 months ago
0
fix PCA pairplot by limiting legend exist only when less than X classes eg 10?
#38
sreichl
closed
3 months ago
0
improve data loading speed with Dask or NumPy
#37
sreichl
opened
9 months ago
0
improve scatter plot speed
#36
sreichl
closed
3 months ago
1
Gene program/marker expression score as metadata
#35
bednarsky
closed
10 months ago
2
PCA fails for large dataset
#34
kvetab
closed
10 months ago
1
reimplement internal cluster indices supporting different metrics and to improve performance
#33
sreichl
opened
1 year ago
0
utilize metadata of interest config field as list for multiple analyses
#32
sreichl
closed
1 year ago
0
add Variation of Information (VI) and Split/Join as external indices
#31
sreichl
opened
1 year ago
0
implement Manifold trustworthiness
#30
sreichl
opened
1 year ago
0
implement significance analysis for clustering
#29
sreichl
opened
1 year ago
1
clustification: add visualization/diagnostics of performance/convergence over time
#28
sreichl
opened
1 year ago
1
Resampling to evaluate clustering stability
#27
bednarsky
opened
1 year ago
0
investigate PCA OOM error with Lee2020NatGenet data
#26
sreichl
closed
1 year ago
0
clustification: test simultaneous merging
#25
sreichl
closed
1 year ago
1
clustree: investigate and implement automatic sc3 stability scoring
#24
sreichl
opened
1 year ago
0
change storing and aggregation of clustering results
#23
sreichl
closed
1 year ago
0
implement consensus cluster calling
#22
sreichl
opened
1 year ago
1
rank all clustering results according to all internal cluster indices using MCDM algorithm
#21
sreichl
closed
1 year ago
0
test & document
#19
sreichl
closed
1 year ago
4
PCA: additional/complementary visualization of top loadings per PC
#18
sreichl
closed
3 months ago
0
release version 1.0.0
#17
sreichl
closed
1 year ago
0
implement meta visualization as an aggregation of all methods (PCA, densMAP, UMAP, …)
#16
sreichl
opened
1 year ago
0
add Dynamic visualization of high-dimensional data
#15
sreichl
opened
1 year ago
0
implement partition based clustering
#14
sreichl
opened
1 year ago
0
Consider alternative clustering algorithms
#13
sreichl
opened
1 year ago
0
clustification: Benchmark clf-based clustering approach
#12
sreichl
opened
1 year ago
5
add quote about clustering to documentation
#11
sreichl
closed
1 year ago
1
implement cluster validation using indices
#10
sreichl
closed
1 year ago
7
implement parameter-free classifier-approach to clustering
#9
sreichl
closed
1 year ago
6
Visualize clustering results using clustree
#8
sreichl
closed
1 year ago
3
Visualize clustering results
#7
sreichl
closed
1 year ago
0
implement HDBSCAN clustering
#6
sreichl
opened
1 year ago
0
implement Leiden clustering
#5
sreichl
closed
1 year ago
4
address slow heatmaps
#4
sreichl
closed
3 months ago
5
check if sklearn PCA automatically standard scales the data
#3
sreichl
closed
3 months ago
1
document all versions in environment yaml specifications
#2
sreichl
closed
1 year ago
0
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