Last updated: 2024-05-13

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Knit directory: lung_lymph_scMultiomics/

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File Version Author Date Message
Rmd 306ddb1 Jing Gu 2024-05-13 wflow_publish("analysis/cross_tissue_DE_u19_fastTopics.Rmd")
html f812a40 Jing Gu 2024-05-09 Build site.
html 68d9e18 Jing Gu 2024-05-09 Build site.
Rmd 7ca45f6 Jing Gu 2024-05-09 cross-tissue comparison
Rmd 7a45261 Jing Gu 2024-05-08 cross-tissue comparison with topic modeling

GoM DE analysis on u19 dataset

Model fitting

Parameters:

N_updates = 150 N_topics = 12

Model evaluation

check the convergence

Version Author Date
68d9e18 Jing Gu 2024-05-09 
Model overview:
  Number of data rows, n: 53647
  Number of data cols, m: 17420
  Rank/number of topics, k: 12
Evaluation of model fit (170 updates performed):
  Poisson NMF log-likelihood: -1.997995557900e+08
  Multinomial topic model log-likelihood: -1.995509032083e+08
  Poisson NMF deviance: +2.634951598369e+08
  Max KKT residual: +1.430262e-02
Set show.size.factors = TRUE, show.mixprops = TRUE and/or show.topic.reps = TRUE in print(...) for more information

Version Author Date
68d9e18 Jing Gu 2024-05-09 
Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` instead.
This warning is displayed once every 8 hours.
Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
generated.

Version Author Date
68d9e18 Jing Gu 2024-05-09

Visualize topics with structural plots

  • plot by cell-types

Version Author Date
68d9e18 Jing Gu 2024-05-09
  • plot by tissue

Version Author Date
68d9e18 Jing Gu 2024-05-09
  • plot by tissue and cell-type

Version Author Date
68d9e18 Jing Gu 2024-05-09

Validate topics with enrichment test

GO enrichemnt test on top 500 genes ranked by loadings

GO enrichemnt test on GoM DE analysis

Identify topics correlated with differences between tissue

  1. test whether any topic is associated with transcriptional differences across tissue \[ L = \beta X_{\text{tissue}} + \text{Covariates} + \epsilon \]
  2. perform T-test to see whether topic proportions between two tissues are significantly different

Density plot for topic proportions between tissue across cell types

X-axis denotes the percentage format of topic proportion. Throughout all the topics, the memberships of cells mainly come from three topics, which are k7, k8, k9. With the cell type labels, we see the distributions of topic proportion separate between tissue at different extent across cell types.

Which cell types show clear separation from visual inspection? * k7: NK, Memory B * k8: Treg, CD4, Th17 * k9: NK, other, Treg, CD8T, Th17

[1] "k1"

[1] "k2"

[1] "k3"

[1] "k4"

[1] "k5"

[1] "k6"

[1] "k7"

[1] "k8"

[1] "k9"

[1] "k10"

[1] "k11"

[1] "k12"

Perform t-test while adjusting for confounders

Procedure

Test mean difference between tissue one donor at a time and then do meta-analysis with Fisher’s method

Results

X-axis denotes cell types and y-axis denotes the topics. For major cell types, we saw majority of topics have significant differences in proportions between tissue.


R version 4.2.0 (2022-04-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS/LAPACK: /software/openblas-0.3.13-el7-x86_64/lib/libopenblas_haswellp-r0.3.13.so

locale:
 [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C         LC_TIME=C           
 [4] LC_COLLATE=C         LC_MONETARY=C        LC_MESSAGES=C       
 [7] LC_PAPER=C           LC_NAME=C            LC_ADDRESS=C        
[10] LC_TELEPHONE=C       LC_MEASUREMENT=C     LC_IDENTIFICATION=C 

attached base packages:
[1] grid      stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
 [1] ComplexHeatmap_2.14.0 colorRamp2_0.1.0      tidyr_1.3.1          
 [4] dplyr_1.1.4           poolr_1.1-1           cowplot_1.1.3        
 [7] ggplot2_3.5.1         fastTopics_0.6-175    Matrix_1.6-5         
[10] workflowr_1.7.1      

loaded via a namespace (and not attached):
  [1] matrixStats_1.2.0   fs_1.6.4            RColorBrewer_1.1-3 
  [4] doParallel_1.0.17   progress_1.2.3      httr_1.4.7         
  [7] rprojroot_2.0.4     tools_4.2.0         bslib_0.7.0        
 [10] DT_0.33             utf8_1.2.4          R6_2.5.1           
 [13] irlba_2.3.5.1       BiocGenerics_0.44.0 uwot_0.2.2         
 [16] lazyeval_0.2.2      colorspace_2.1-0    GetoptLong_1.0.5   
 [19] withr_3.0.0         tidyselect_1.2.1    prettyunits_1.2.0  
 [22] processx_3.8.3      compiler_4.2.0      git2r_0.33.0       
 [25] cli_3.6.2           Cairo_1.6-2         plotly_4.10.4      
 [28] labeling_0.4.3      sass_0.4.9          scales_1.3.0       
 [31] SQUAREM_2021.1      quadprog_1.5-8      callr_3.7.3        
 [34] pbapply_1.7-2       mixsqp_0.3-54       stringr_1.5.1      
 [37] digest_0.6.35       rmarkdown_2.26      RhpcBLASctl_0.23-42
 [40] pkgconfig_2.0.3     htmltools_0.5.8.1   highr_0.10         
 [43] fastmap_1.1.1       invgamma_1.1        GlobalOptions_0.1.2
 [46] htmlwidgets_1.6.4   rlang_1.1.3         rstudioapi_0.15.0  
 [49] farver_2.1.1        shape_1.4.6         jquerylib_0.1.4    
 [52] generics_0.1.3      jsonlite_1.8.8      crosstalk_1.2.1    
 [55] gtools_3.9.5        magrittr_2.0.3      S4Vectors_0.36.2   
 [58] Rcpp_1.0.12         munsell_0.5.1       fansi_1.0.6        
 [61] lifecycle_1.0.4     stringi_1.7.6       whisker_0.4.1      
 [64] yaml_2.3.8          mathjaxr_1.6-0      Rtsne_0.17         
 [67] parallel_4.2.0      promises_1.3.0      ggrepel_0.9.5      
 [70] crayon_1.5.2        lattice_0.22-5      circlize_0.4.15    
 [73] hms_1.1.3           knitr_1.46          ps_1.7.6           
 [76] pillar_1.9.0        rjson_0.2.21        stats4_4.2.0       
 [79] codetools_0.2-19    glue_1.7.0          evaluate_0.23      
 [82] getPass_0.2-2       data.table_1.15.4   RcppParallel_5.1.7 
 [85] vctrs_0.6.5         png_0.1-8           httpuv_1.6.14      
 [88] foreach_1.5.2       gtable_0.3.5        purrr_1.0.2        
 [91] clue_0.3-65         ashr_2.2-63         cachem_1.0.8       
 [94] xfun_0.43           later_1.3.2         viridisLite_0.4.2  
 [97] truncnorm_1.0-9     tibble_3.2.1        iterators_1.0.14   
[100] IRanges_2.32.0      cluster_2.1.6