library(PALMO)
#> Loading required package: grid

Introduction

PALMO (Platform for Analyzing Longitudinal Multi-omics data) is a platform for anayzing longitudinal data from bulk as well as single cell. It allows to identify inter-, intra-donor variations in genes over longitudinal time points. The analysis can be done on bulk expression dataset without known celltype information or single cell with celltype/user-defined groups. It allows to infer stable and variable features in given donor and each celltype (or user defined group). The outlier analysis can be performed to identify technical/biological perturbed samples in donor/participant. Further, differential analysis can be performed to decipher time-wise changes in gene expression in a celltype.


img
General workflow and analysis schema of PALMO. It can work with longitudinal data obtained from bulk such as clinical, bulk RNAseq, proteomic or single cell dataset from scRNAseq, and scATACseq.

Install package and load library

To install library, simply run

library("devtools")
install_github("aifimmunology/PALMO")
library("PALMO")

Tutorials

There are couple of tutorials presented to help users to run PALMO on bulk and single cell data. The tutorials can be found at [https://github.com/aifimmunology/PALMO/blob/main/ReferenceManual-PALMO-v0.1.1.pdf]. The examples includes:

Authors

Suhas Vasaikar, Aarthi talla and Xiaojun Li designed the PALMO algorithm. Suhas Vasaikar implemented the PALMO package.

License

PALM is licensed under the MIT-License.

Session info

sessionInfo()
#> R version 4.0.3 (2020-10-10)
#> Platform: x86_64-apple-darwin17.0 (64-bit)
#> Running under: macOS Big Sur 10.16
#> 
#> Matrix products: default
#> BLAS:   /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
#> LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
#> 
#> locale:
#> [1] C/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#> 
#> attached base packages:
#> [1] grid      stats     graphics  grDevices utils     datasets  methods  
#> [8] base     
#> 
#> other attached packages:
#> [1] PALMO_0.1.2
#> 
#> loaded via a namespace (and not attached):
#>   [1] readxl_1.3.1                backports_1.2.0            
#>   [3] circlize_0.4.11             plyr_1.8.6                 
#>   [5] igraph_1.2.8                lazyeval_0.2.2             
#>   [7] splines_4.0.3               listenv_0.8.0              
#>   [9] scattermore_0.7             GenomeInfoDb_1.24.2        
#>  [11] ggplot2_3.3.5               digest_0.6.28              
#>  [13] htmltools_0.5.2             fansi_0.5.0                
#>  [15] magrittr_2.0.1              tensor_1.5                 
#>  [17] cluster_2.1.0               ROCR_1.0-11                
#>  [19] readr_1.4.0                 ComplexHeatmap_2.4.3       
#>  [21] globals_0.14.0              modelr_0.1.8               
#>  [23] matrixStats_0.61.0          colorspace_2.0-2           
#>  [25] rvest_0.3.6                 blob_1.2.1                 
#>  [27] ggrepel_0.9.1               haven_2.3.1                
#>  [29] xfun_0.30                   dplyr_1.0.7                
#>  [31] RCurl_1.98-1.2              crayon_1.4.2               
#>  [33] jsonlite_1.7.2              lme4_1.1-25                
#>  [35] spatstat_1.64-1             spatstat.data_2.1-0        
#>  [37] survival_3.2-7              zoo_1.8-9                  
#>  [39] glue_1.6.2                  polyclip_1.10-0            
#>  [41] gtable_0.3.0                zlibbioc_1.34.0            
#>  [43] XVector_0.28.0              leiden_0.3.9               
#>  [45] DelayedArray_0.14.1         GetoptLong_1.0.4           
#>  [47] SingleCellExperiment_1.10.1 future.apply_1.8.1         
#>  [49] shape_1.4.5                 BiocGenerics_0.34.0        
#>  [51] abind_1.4-5                 scales_1.1.1               
#>  [53] pheatmap_1.0.12             DBI_1.1.0                  
#>  [55] miniUI_0.1.1.1              Rcpp_1.0.7                 
#>  [57] viridisLite_0.4.0           xtable_1.8-4               
#>  [59] clue_0.3-57                 reticulate_1.22            
#>  [61] stats4_4.0.3                htmlwidgets_1.5.4          
#>  [63] httr_1.4.2                  RColorBrewer_1.1-2         
#>  [65] ellipsis_0.3.2              Seurat_4.0.0               
#>  [67] factoextra_1.0.7.999        ica_1.0-2                  
#>  [69] farver_2.1.0                pkgconfig_2.0.3            
#>  [71] sass_0.4.0                  uwot_0.1.10                
#>  [73] dbplyr_1.4.4                deldir_1.0-6               
#>  [75] utf8_1.2.2                  tidyselect_1.1.1           
#>  [77] rlang_1.0.2                 reshape2_1.4.4             
#>  [79] later_1.3.0                 cellranger_1.1.0           
#>  [81] munsell_0.5.0               tools_4.0.3                
#>  [83] cli_3.2.0                   generics_0.1.3             
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#>  [87] evaluate_0.15               stringr_1.4.0              
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#>  [97] pbapply_1.5-0               future_1.23.0              
#>  [99] nlme_3.1-149                mime_0.12                  
#> [101] xml2_1.3.2                  compiler_4.0.3             
#> [103] rstudioapi_0.13             plotly_4.10.0              
#> [105] png_0.1-7                   spatstat.utils_2.2-0       
#> [107] reprex_0.3.0                tweenr_1.0.1               
#> [109] tibble_3.1.6                statmod_1.4.35             
#> [111] bslib_0.3.1                 stringi_1.7.5              
#> [113] forcats_0.5.0               lattice_0.20-41            
#> [115] Matrix_1.3-4                nloptr_1.2.2.2             
#> [117] vctrs_0.4.0                 pillar_1.7.0               
#> [119] lifecycle_1.0.1             lmtest_0.9-39              
#> [121] jquerylib_0.1.4             GlobalOptions_0.1.2        
#> [123] RcppAnnoy_0.0.19            bitops_1.0-7               
#> [125] data.table_1.14.2           cowplot_1.1.1              
#> [127] irlba_2.3.3                 GenomicRanges_1.40.0       
#> [129] httpuv_1.6.3                patchwork_1.1.1            
#> [131] R6_2.5.1                    promises_1.2.0.1           
#> [133] KernSmooth_2.23-17          gridExtra_2.3              
#> [135] IRanges_2.22.2              parallelly_1.28.1          
#> [137] codetools_0.2-16            boot_1.3-25                
#> [139] MASS_7.3-53                 assertthat_0.2.1           
#> [141] SummarizedExperiment_1.18.2 MAST_1.14.0                
#> [143] rjson_0.2.20                SeuratObject_4.0.2         
#> [145] sctransform_0.3.2           GenomeInfoDbData_1.2.3     
#> [147] S4Vectors_0.26.1            mgcv_1.8-33                
#> [149] parallel_4.0.3              hms_0.5.3                  
#> [151] rpart_4.1-15                tidyverse_1.3.0            
#> [153] tidyr_1.1.4                 minqa_1.2.4                
#> [155] rmarkdown_2.15              Rtsne_0.15                 
#> [157] ggforce_0.3.2               Biobase_2.48.0             
#> [159] lubridate_1.7.9             shiny_1.7.1