Run GLMPCA (generalized version of principal components analysis)

Run GLMPCA (generalized version of principal components analysis)

Usage

RunGLMPCA(object, ...)

# S3 method for class 'Seurat'
RunGLMPCA(
  object,
  assay = NULL,
  layer = "counts",
  features = NULL,
  L = 5,
  fam = c("poi", "nb", "nb2", "binom", "mult", "bern"),
  rev.gmlpca = FALSE,
  ndims.print = 1:5,
  nfeatures.print = 30,
  reduction.name = "glmpca",
  reduction.key = "GLMPC_",
  verbose = TRUE,
  seed.use = 11,
  ...
)

# S3 method for class 'Assay'
RunGLMPCA(
  object,
  assay = NULL,
  layer = "counts",
  features = NULL,
  L = 5,
  fam = c("poi", "nb", "nb2", "binom", "mult", "bern"),
  rev.gmlpca = FALSE,
  ndims.print = 1:5,
  nfeatures.print = 30,
  reduction.key = "GLMPC_",
  verbose = TRUE,
  seed.use = 11,
  ...
)

# S3 method for class 'Assay5'
RunGLMPCA(
  object,
  assay = NULL,
  layer = "counts",
  features = NULL,
  L = 5,
  fam = c("poi", "nb", "nb2", "binom", "mult", "bern"),
  rev.gmlpca = FALSE,
  ndims.print = 1:5,
  nfeatures.print = 30,
  reduction.key = "GLMPC_",
  verbose = TRUE,
  seed.use = 11,
  ...
)

# Default S3 method
RunGLMPCA(
  object,
  assay = NULL,
  layer = "counts",
  features = NULL,
  L = 5,
  fam = c("poi", "nb", "nb2", "binom", "mult", "bern"),
  rev.gmlpca = FALSE,
  ndims.print = 1:5,
  nfeatures.print = 30,
  reduction.key = "GLMPC_",
  verbose = TRUE,
  seed.use = 11,
  ...
)

Arguments

object

An object. This can be a Seurat object, an assay object, or a matrix-like object.

...

Additional arguments to be passed to the glmpca::glmpca function.

assay

A character string specifying the assay to be used for the analysis. Default is NULL.

layer

A character string specifying the layer to be used for the analysis. Default is "counts".

features

A character vector specifying the features to be used for the analysis. Default is NULL, which uses all variable features.

L

An integer specifying the number of components to be computed. Default is 5.

fam

A character string specifying the family of the generalized linear model to be used. Currently supported values are "poi", "nb", "nb2", "binom", "mult", and "bern". Default is "poi".

rev.gmlpca

A logical value indicating whether to perform reverse GLMPCA (i.e., transpose the input matrix) before running the analysis. Default is FALSE.

ndims.print

An integer vector specifying the dimensions (number of components) to print in the output. Default is 1:5.

nfeatures.print

An integer specifying the number of features to print in the output. Default is 30.

reduction.name

A character string specifying the name of the reduction to be stored in the Seurat object. Default is "glmpca".

reduction.key

A character string specifying the prefix for the column names of the basis vectors. Default is "GLMPC_".

verbose

A logical value indicating whether to print verbose output. Default is TRUE.

seed.use

An integer specifying the random seed to be used. Default is 11.

Examples

pancreas_sub <- RunGLMPCA(object = pancreas_sub)
#> ℹ [2025-07-02 03:00:49] GLMPC_ 1 
#> Positive:  Ncan, L1cam, S100g, Bhlhe23, Ppy, AI854703, Onecut3, C8b, Gm13613, Gsdma2 
#> 	   Chrna3, Ina, Slc4a10, Crmp1, Efcab6, Otc, Ifit1bl1, Gabrg2, Hspa1a, Adamts18 
#> 	   Syt4, Galnt9, Islr2, Adgrv1, Crtac1, Nkx6-3, Tmem252, Col19a1, Fbxl2, Gast 
#> Negative:  Slc34a2, Bmp3, Il1r2, Nipal4, Tmem100, Krt17, P2ry2, Rarres2, RP23-53O7.2, Tnni3 
#> 	   Upk3b, Ptgfr, 1700001L19Rik, Aldh1a7, Eppin, Ctgf, Plscr2, Aldh1a2, Xkr5, Napsa 
#> 	   Edn1, Mmp7, Myo1h, Wnt5a, Slc22a2, 4930524B15Rik, Nlgn1, Lce6a, Rpp25, Prr5l 
#> GLMPC_ 2 
#> Positive:  Sostdc1, Tmem255b, Gm26808, Dlgap1, Mapk11, Lix1, Gabra1, Pkd2l1, Tfap2c, Aldh1a7 
#> 	   Bhlhe23, Plxnd1, Timp3, A730017C20Rik, E130114P18Rik, Fgf21, Grin3a, Snai2, 2210407C18Rik, 1700001L19Rik 
#> 	   Siglece, Atoh8, Cldn1, Sds, Snhg11, Fgf18, Sncg, Slc4a1, Fgf13, Bhmt2 
#> Negative:  Il1r2, Gast, Nlgn1, RP23-53O7.2, Car3, Platr26, Speer4c, Slco1a6, Kcnj13, Prl 
#> 	   Rgs4, Gm20554, Aard, Gabrg2, March11, Foxd3, Foxc1, Wdr20rt, Trpc5, D130043K22Rik 
#> 	   Meikin, Onecut3, 4930426D05Rik, Tnfaip8l3, Hspa1a, Bmp3, Slc30a8, Cartpt, Gm13613, Adgrv1 
#> GLMPC_ 3 
#> Positive:  Sycp3, Siglech, Fgf8, Cnksr2, Ckm, Lypd1, Rrad, Gdf15, Gm10382, Gm26522 
#> 	   Gm42637, Chil5, Nr2f2, Fam162b, Glod5, Rad54l, Stmn1, Etv4, Serpina1c, Hist4h4 
#> 	   Vsig8, Gm26532, Rsph4a, Akna, Megf6, Nhlh1, Hist1h1b, Rin3, Serpina1e, BC039966 
#> Negative:  Bmp3, Col19a1, Mapk11, Cntn1, Il1r2, Nipal4, Npy, Sostdc1, Sst, Slc34a2 
#> 	   Myo1h, Dlgap1, Tmem100, S100g, Aldh1a7, Klhl14, Ppy, Ppp1r27, F730016J06Rik, 1700001L19Rik 
#> 	   Krt17, RP23-53O7.2, Fgb, Gm17767, Cldn1, Tmem255b, Gm13613, Gm26808, Iapp, Ins1 
#> GLMPC_ 4 
#> Positive:  Col19a1, Gcg, Bhlhe23, F730016J06Rik, Krt33b, Fgb, Vipr1, Thbd, Aldh1a7, Slc34a2 
#> 	   Tfap2c, Snhg7os, Necab3, Upk3b, Fmod, Ghrl, Nkx6-3, Fgf8, Pou6f2, Parp3 
#> 	   Pdcd1, Trim29, Ppp1r3b, Gast, C8b, Cd2, Serpina1a, Ppp1r27, Slc4a1, Cym 
#> Negative:  Sst, Cldn1, Mapk11, Npy, 1700016F12Rik, Slc2a3, Irx3, Myo1h, Chrna3, Etv4 
#> 	   Slc9a5, Kcnk10, Prl, Syndig1l, Rasgef1c, Tcerg1l, Mapk12, M1ap, Dscam, Dpysl3 
#> 	   Arl14, Gm38037, Prima1, Cxcl10, Frzb, Ins2, Chrnb4, Fgf13, A730017C20Rik, Fam159b 
#> GLMPC_ 5 
#> Positive:  Gm17455, Nid1, Ghrl, Avpr1b, Ngf, Irs4, Foxd3, Nkx6-3, Sst, Cntn1 
#> 	   Fgf21, Slc9a5, Bmp3, Spata20, Speer4c, Arhgap22, Ifit1bl1, Irx3, Mboat4, Car3 
#> 	   Kcnk10, Onecut3, Lrrtm3, Ctnna3, Isg15, Gast, Acsl1, St8sia2, Dscam, Cldn1 
#> Negative:  D130043K22Rik, Gabrg2, Ins1, Ppp1r27, S100g, Gm38112, Col19a1, Nes, Slc4a1, 2410021H03Rik 
#> 	   Cdkn2c, Nipal4, Krt33b, Xkr5, Iqgap3, Rpp25, Ins2, Gm38037, Napsa, Fbxl2 
#> 	   E030037K01Rik, Brca1, Aurkb, Pif1, Bcas3os2, Cbln1, Adra2c, Tmem215, Arhgap36, Mxd3 
CellDimPlot(
  pancreas_sub,
  group.by = "CellType",
  reduction = "glmpca"
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's fill values.