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[ ![ codecov] ( https://codecov.io/gh/jr-leary7/scLANE/branch/main/graph/badge.svg?token=U2U5RTF2VW )] ( https://codecov.io/gh/jr-leary7/scLANE )
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- [ ![ DOI] ( https://img.shields.io/static/v1?label=DOI&message=10.5281/zenodo.10182497 &color=blue )] ( https://doi.org/10.5281/zenodo.10182497 )
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<!-- badges: end -->
@@ -172,12 +172,12 @@ scLANE_models_glm <- testDynamic(sim_data,
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pt = order_df ,
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genes = gene_sample ,
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size.factor.offset = cell_offset ,
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- n.cores = 4 ,
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+ n.cores = 4L ,
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verbose = FALSE )
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# > Registered S3 method overwritten by 'bit':
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# > method from
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# > print.ri gamlss
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- # > scLANE testing completed for 100 genes across 1 lineage in 45.702 secs
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+ # > scLANE testing completed for 100 genes across 1 lineage in 35.37 secs
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```
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After the function finishes running, we use ` getResultsDE() ` to generate
@@ -195,13 +195,13 @@ select(scLANE_res_glm, Gene, Lineage, Test_Stat, P_Val, P_Val_Adj, Gene_Dynamic_
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col.names = c(" Gene" , " Lineage" , " LRT stat." , " P-value" , " Adj. p-value" , " Predicted dynamic status" ))
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```
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- | Gene | Lineage | LRT stat. | P-value | Adj. p-value | Predicted dynamic status |
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- | :---------| :--------| ----------:| --------:| -------------:| -------------------------:|
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- | MFSD2B | A | 216.750 | 0.000 | 0.000 | 1 |
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- | RPL29 | A | 5.632 | 0.018 | 0.353 | 0 |
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- | UAP1L1 | A | 9.880 | 0.007 | 0.157 | 0 |
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- | TMCO3 | A | 167.709 | 0.000 | 0.000 | 1 |
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- | GOLGA8EP | A | 4.359 | 0.037 | 0.487 | 0 |
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+ | Gene | Lineage | LRT stat. | P-value | Adj. p-value | Predicted dynamic status |
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+ | :----------- | :--------| ----------:| --------:| -------------:| -------------------------:|
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+ | RAB1B | A | 219.950 | 0.000 | 0.000 | 1 |
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+ | LY75.CD302 | A | 4.858 | 0.028 | 0.541 | 0 |
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+ | UAP1L1 | A | 9.894 | 0.007 | 0.163 | 0 |
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+ | TMCO3 | A | 167.311 | 0.000 | 0.000 | 1 |
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+ | GOLGA8EP | A | 4.201 | 0.040 | 0.567 | 0 |
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### GEE mode
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@@ -222,9 +222,9 @@ scLANE_models_gee <- testDynamic(sim_data,
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is.gee = TRUE ,
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id.vec = sim_data $ subject ,
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cor.structure = " ar1" ,
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- n.cores = 4 ,
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+ n.cores = 4L ,
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verbose = FALSE )
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- # > scLANE testing completed for 100 genes across 1 lineage in 2.201 mins
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+ # > scLANE testing completed for 100 genes across 1 lineage in 1.525 mins
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```
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We again generate the table of DE test results. The variance of the
@@ -242,11 +242,11 @@ select(scLANE_res_gee, Gene, Lineage, Test_Stat, P_Val, P_Val_Adj, Gene_Dynamic_
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| Gene | Lineage | Wald stat. | P-value | Adj. p-value | Predicted dynamic status |
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| :---------| :--------| -----------:| --------:| -------------:| -------------------------:|
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- | DGUOK | A | 64351.893 | 0 | 0 | 1 |
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- | TBCC | A | 32.151 | 0 | 0 | 1 |
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+ | DGUOK | A | 200675.460 | 0 | 0 | 1 |
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+ | TBCC | A | 40.399 | 0 | 0 | 1 |
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| GOLGA8EP | A | NA | NA | NA | 0 |
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- | TMC6 | A | 5052.168 | 0 | 0 | 1 |
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- | JARID2 | A | 1512.240 | 0 | 0 | 1 |
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+ | EMC3 | A | 8397.337 | 0 | 0 | 1 |
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+ | DDX41 | A | 3486.998 | 0 | 0 | 1 |
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### GLMM mode
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@@ -267,11 +267,10 @@ scLANE_models_glmm <- testDynamic(sim_data,
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size.factor.offset = cell_offset ,
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n.potential.basis.fns = 3 ,
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is.glmm = TRUE ,
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- glmm.adaptive = TRUE ,
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id.vec = sim_data $ subject ,
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- n.cores = 4 ,
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+ n.cores = 4L ,
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verbose = FALSE )
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- # > scLANE testing completed for 100 genes across 1 lineage in 2.968 mins
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+ # > scLANE testing completed for 100 genes across 1 lineage in 3.133 mins
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```
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** Note:** The GLMM mode is still under development, as we are working on
@@ -291,13 +290,13 @@ select(scLANE_res_glmm, Gene, Lineage, Test_Stat, P_Val, P_Val_Adj, Gene_Dynamic
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col.names = c(" Gene" , " Lineage" , " LRT stat." , " P-value" , " Adj. p-value" , " Predicted dynamic status" ))
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```
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- | Gene | Lineage | LRT stat. | P-value | Adj. p-value | Predicted dynamic status |
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- | :-------- | :--------| ----------:| --------:| -------------:| -------------------------:|
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- | DDX1 | A | 132.422 | 0.000 | 0 | 1 |
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- | GGNBP2 | A | 73.683 | 0.000 | 0 | 1 |
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- | WDSUB1 | A | NA | NA | NA | 0 |
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- | FAM135B | A | NA | NA | NA | 0 |
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- | DAB1 | A | 9.217 | 0.684 | 1 | 0 |
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+ | Gene | Lineage | LRT stat. | P-value | Adj. p-value | Predicted dynamic status |
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+ | :-------| :--------| ----------:| --------:| -------------:| -------------------------:|
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+ | VDAC1 | A | 205.644 | 0.000 | 0 | 1 |
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+ | CKAP4 | A | 139.246 | 0.000 | 0 | 1 |
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+ | MRTO4 | A | 5.048 | 0.998 | 1 | 0 |
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+ | FOXD3 | A | 2.586 | 1.000 | 1 | 0 |
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+ | UBE2Q1 | A | 94.077 | 0.000 | 0 | 1 |
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## Downstream analysis & visualization
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