Getting Started with Kompot¶
Kompot finds genes whose expression changes between two conditions at single-cell resolution. It fits Gaussian-process models over a continuous cell-state representation and scores each gene with a Mahalanobis distance that accounts for expression covariance, so it detects coordinated, trajectory-aware changes that per-cluster tests miss.
This front-door tutorial runs differential expression (DE) end to end and visualizes the result. The method and its derivation live in the paper.
Dive deeper: Advanced DE options · DE with sample variance · Differential abundance
We compare bone marrow from Young vs. Old mice.
[1]:
%matplotlib inline
import anndata as ad
import matplotlib.pyplot as plt
import numpy as np
import palantir
import pandas as pd
import scanpy as sc
import kompot
# Consistent, clean plotting style across the tutorial set
plt.rcParams["axes.spines.right"] = False
plt.rcParams["axes.spines.top"] = False
plt.rcParams["image.cmap"] = "Spectral_r"
Configuration¶
Everything you would adapt for your own data lives here:
[2]:
DATA_PATH = "../data/murine_bone_marrow_aging.h5ad"
GROUPING_COLUMN = "Age" # condition column in adata.obs
CONDITIONS = ["Young", "Old"] # first entry is the reference
CELL_TYPE_COLUMN = "highres_celltype" # for visualization only
DIMENSIONALITY_REDUCTION = "DM_EigenVectors" # cell-state representation
LAYER_FOR_EXPRESSION = "logged_counts" # expression layer
Load Data¶
The dataset downloads automatically from Zenodo on first run:
[3]:
import os
from pathlib import Path
import requests
from tqdm.auto import tqdm
Path(DATA_PATH).parent.mkdir(parents=True, exist_ok=True)
if not os.path.exists(DATA_PATH):
print("Downloading dataset (~2.4 GB) from Zenodo ...")
url = "https://zenodo.org/records/15587768/files/murine_bone_marrow_aging.h5ad?download=1"
response = requests.get(url, stream=True)
total = int(response.headers.get("content-length", 0))
with open(DATA_PATH, "wb") as file, tqdm(total=total, unit="B", unit_scale=True) as bar:
for chunk in response.iter_content(chunk_size=1 << 20):
file.write(chunk)
bar.update(len(chunk))
adata = ad.read_h5ad(DATA_PATH)
adata
[3]:
AnnData object with n_obs × n_vars = 8090 × 16285
obs: 'Compartment', 'Replicate', 'Age', 'Sample', 'Info', 'batch', 'doublet_score', 'n_genes_by_counts', 'total_counts', 'total_counts_mt', 'pct_counts_mt', 'total_counts_hb', 'pct_counts_hb', 'S_score', 'G2M_score', 'phase', 'leiden', 'phenograph', 'highres_celltype', 'midres_celltype'
var: 'gene_ids', 'feature_types', 'genome', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts', 'hb', 'highly_variable', 'means', 'dispersions', 'dispersions_norm', 'highly_variable_nbatches', 'highly_variable_intersection'
uns: 'Age_colors', 'Compartment_colors', 'DMEigenValues', 'DM_EigenValues', 'Info_colors', 'README', 'Replicate_colors', 'Sample_colors', 'batch_colors', 'draw_graph', 'highres_celltype_colors', 'hvg', 'leiden', 'leiden_colors', 'midres_celltype_colors', 'neighbors', 'pca', 'phase_colors', 'umap'
obsm: 'AbCapture', 'DM_EigenVectors', 'HTO', 'X_draw_graph_fa', 'X_pca', 'X_pca_harmony', 'X_pca_noregression', 'X_umap'
varm: 'PCs'
layers: 'MAGIC_imputed_data', 'cc_counts', 'logged_counts', 'normalized_counts', 'raw_counts'
obsp: 'DM_Kernel', 'DM_Similarity', 'connectivities', 'distances'
A quick look at the cell types and the two conditions:
[4]:
sc.pl.umap(adata, color=[CELL_TYPE_COLUMN, GROUPING_COLUMN], frameon=False, wspace=1.3)
Kompot needs a continuous cell-state representation. Palantir diffusion maps capture the geometry of differentiation while denoising:
[5]:
palantir.utils.run_diffusion_maps(adata, pca_key="X_pca_harmony", n_components=40);
Differential Expression¶
One call fits the models, scores every gene, and calibrates an FDR against a null of shuffled genes. See `kompot.de <https://kompot.readthedocs.io/en/latest/simplified.html#kompot.de>`__.
[6]:
de_results = kompot.de(
adata,
groupby=GROUPING_COLUMN,
condition1=CONDITIONS[0],
condition2=CONDITIONS[1],
layer=LAYER_FOR_EXPRESSION,
obsm_key=DIMENSIONALITY_REDUCTION,
gp=kompot.GPSettings(batch_size=0), # 0 = all cells at once; raise for lower memory
)
[2026-07-11 00:55:01,796] [INFO ] Condition 1 (Young): 2,917 cells
[2026-07-11 00:55:01,796] [INFO ] Condition 2 (Old): 3,116 cells
[2026-07-11 00:55:06,585] [INFO ] Fitting expression estimator for condition 1...
[2026-07-11 00:55:34,589] [INFO ] Fitting expression estimator for condition 2...
[2026-07-11 00:56:41,559] [INFO ] FDR analysis complete: 192/16285 genes significantly DE at FDR < 0.05
[2026-07-11 00:56:41,561] [INFO ] Mahalanobis distance threshold for FDR < 0.05: 5.8215
[2026-07-11 00:56:48,460] [INFO ] This run will have `run_id=0`.
Results land in adata.var. The key columns (for Young→Old):
kompot_de_Young_to_Old_mean_lfc— mean log fold changekompot_de_Young_to_Old_mahalanobis— significance (higher = stronger)kompot_de_Young_to_Old_is_de— significant at FDR < 0.05
[7]:
c1, c2 = CONDITIONS
mahal = f"kompot_de_{c1}_to_{c2}_mahalanobis"
adata.var.loc[:, adata.var.columns.str.contains("kompot_de")] \
.sort_values(mahal, ascending=False).head(20)
[7]:
| kompot_de_Young_to_Old_mahalanobis | kompot_de_Young_to_Old_mean_lfc | kompot_de_Young_to_Old_mahalanobis_local_fdr | kompot_de_Young_to_Old_is_de | |
|---|---|---|---|---|
| H2-Q7 | 15.224920 | 0.371810 | 1.283086e-141 | True |
| Cd74 | 12.781286 | 0.105968 | 1.641235e-80 | True |
| H2-Aa | 12.641082 | 0.142574 | 2.138046e-77 | True |
| H2-Ab1 | 12.307942 | 0.153822 | 1.587455e-70 | True |
| Igkc | 11.416240 | 0.016244 | 1.449789e-53 | True |
| H2-Eb1 | 11.371004 | 0.123908 | 8.317497e-53 | True |
| AW112010 | 11.366238 | 0.238251 | 1.114925e-52 | True |
| S100a9 | 10.385744 | -0.051261 | 5.227253e-37 | True |
| Ifitm3 | 10.134062 | 0.110643 | 1.495802e-33 | True |
| S100a8 | 10.089391 | -0.049699 | 5.666282e-33 | True |
| H2-Q6 | 9.790485 | 0.235504 | 4.653679e-29 | True |
| Cd52 | 9.649612 | -0.038509 | 2.354785e-27 | True |
| Aldh1a1 | 9.493316 | 0.147759 | 1.680922e-25 | True |
| Ifitm1 | 9.438788 | 0.128764 | 7.277426e-25 | True |
| Ifitm2 | 9.357804 | 0.086038 | 5.729708e-24 | True |
| Ighm | 9.204495 | -0.052318 | 3.048729e-22 | True |
| Cd79a | 9.182240 | -0.001314 | 5.438490e-22 | True |
| Apoe | 9.142740 | -0.039501 | 1.452210e-21 | True |
| Fos | 8.999856 | 0.159999 | 4.706724e-20 | True |
| Gm47283 | 8.930669 | 0.188797 | 2.573649e-19 | True |
Volcano plot¶
Effect size vs. significance, one point per gene (`volcano_de <https://kompot.readthedocs.io/en/latest/plotting.html#kompot.plot.volcano_de>`__):
[8]:
kompot.plot.volcano_de(adata)
[2026-07-11 00:56:49,080] [INFO ] Found DE run info for run_id=-1
[2026-07-11 00:56:49,081] [INFO ] Found mean_lfc_key='kompot_de_Young_to_Old_mean_lfc' from run info
[2026-07-11 00:56:49,081] [INFO ] Found mahalanobis_key='kompot_de_Young_to_Old_mahalanobis' from run info
[2026-07-11 00:56:49,083] [INFO ] Successfully inferred fields: {'mean_lfc_key': 'kompot_de_Young_to_Old_mean_lfc', 'mahalanobis_key': 'kompot_de_Young_to_Old_mahalanobis'}
[2026-07-11 00:56:49,084] [INFO ] Using DE run 0: comparing Young to Old
[2026-07-11 00:56:49,095] [INFO ] Using data columns from var - lfc: 'kompot_de_Young_to_Old_mean_lfc', score: 'kompot_de_Young_to_Old_mahalanobis'
[2026-07-11 00:56:49,103] [INFO ] Highlighting 192 genes marked as DE (109 up, 83 down)
[2026-07-11 00:56:49,119] [INFO ] Labeling top 10 genes by score
Highlight gene sets of interest with custom colors and labels:
[9]:
gene_sets = [
{"name": "MHC class II", "genes": ["H2-Ab1", "H2-Aa", "Cd74", "H2-Eb1"], "color": "#E76F51"},
{"name": "Antioxidant", "genes": ["S100a8", "S100a9", "Mgst1", "Apoe", "Hp"], "color": "#2A9D8F"},
]
# keep only genes present in this dataset
for gs in gene_sets:
gs["genes"] = [g for g in gs["genes"] if g in adata.var_names]
kompot.plot.volcano_de(
adata,
highlight_genes=gene_sets,
gene_labels=[g for gs in gene_sets for g in gs["genes"]],
)
[2026-07-11 00:56:49,426] [INFO ] Found DE run info for run_id=-1
[2026-07-11 00:56:49,426] [INFO ] Found mean_lfc_key='kompot_de_Young_to_Old_mean_lfc' from run info
[2026-07-11 00:56:49,427] [INFO ] Found mahalanobis_key='kompot_de_Young_to_Old_mahalanobis' from run info
[2026-07-11 00:56:49,428] [INFO ] Successfully inferred fields: {'mean_lfc_key': 'kompot_de_Young_to_Old_mean_lfc', 'mahalanobis_key': 'kompot_de_Young_to_Old_mahalanobis'}
[2026-07-11 00:56:49,429] [INFO ] Using DE run 0: comparing Young to Old
[2026-07-11 00:56:49,437] [INFO ] Using data columns from var - lfc: 'kompot_de_Young_to_Old_mean_lfc', score: 'kompot_de_Young_to_Old_mahalanobis'
[2026-07-11 00:56:49,440] [INFO ] Added highlight group 'MHC class II' with 4 genes
[2026-07-11 00:56:49,441] [INFO ] Added highlight group 'Antioxidant' with 5 genes
[2026-07-11 00:56:49,455] [INFO ] Labeling 9 specific genes
Where the signal sits¶
Project a top gene’s smoothed expression and fold change back onto the UMAP with `plot_gene_expression <https://kompot.readthedocs.io/en/latest/plotting.html#kompot.plot.plot_gene_expression>`__:
[10]:
top_gene = adata.var[mahal].idxmax()
kompot.plot.plot_gene_expression(adata, gene=top_gene, frameon=False)
[2026-07-11 00:56:49,733] [INFO ] Found DE run info for run_id=-1
[2026-07-11 00:56:49,734] [INFO ] Found mean_lfc_key='kompot_de_Young_to_Old_mean_lfc' from run info
[2026-07-11 00:56:49,734] [INFO ] Found mahalanobis_key='kompot_de_Young_to_Old_mahalanobis' from run info
[2026-07-11 00:56:49,736] [INFO ] Successfully inferred fields: {'mean_lfc_key': 'kompot_de_Young_to_Old_mean_lfc', 'mahalanobis_key': 'kompot_de_Young_to_Old_mahalanobis'}
[2026-07-11 00:56:49,737] [INFO ] Using DE run 0: comparing Young to Old
[2026-07-11 00:56:49,737] [INFO ] Using fields for gene expression plot - lfc_key: 'kompot_de_Young_to_Old_mean_lfc', score_key: 'kompot_de_Young_to_Old_mahalanobis'
[2026-07-11 00:56:49,738] [INFO ] Using layer 'logged_counts' inferred from run information
[2026-07-11 00:56:49,741] [INFO ] Using smoothed layer 'kompot_de_Young_smoothed' for 'Young'
[2026-07-11 00:56:49,741] [INFO ] Using smoothed layer 'kompot_de_Old_smoothed' for 'Old'
[2026-07-11 00:56:49,742] [INFO ] Using fold_change layer 'kompot_de_Young_to_Old_fold_change' from run_info
Fold-change heatmap¶
The top genes summarized per cell type. fold_change_mode=True shows the log fold change directly (`heatmap <https://kompot.readthedocs.io/en/latest/plotting.html#kompot.plot.heatmap>`__):
[11]:
genes = adata.var[mahal].sort_values(ascending=False).head(20).index
kompot.plot.heatmap(
adata,
genes=genes,
groupby=CELL_TYPE_COLUMN,
exclude_groups="Plasma cell", # too few cells to summarize reliably
vmin="p1", vmax="p99", # clip color scale to 1st/99th percentile
fold_change_mode=True,
)
[2026-07-11 00:56:50,819] [INFO ] Inferred condition_column='Age' from run information
[2026-07-11 00:56:50,820] [INFO ] Inferred condition1='Young' from run information
[2026-07-11 00:56:50,821] [INFO ] Inferred condition2='Old' from run information
[2026-07-11 00:56:50,821] [INFO ] Inferred layer='logged_counts' from run information
[2026-07-11 00:56:50,822] [INFO ] Creating fold change heatmap with 20 genes/features
[2026-07-11 00:56:50,823] [INFO ] Using expression data from layer: 'logged_counts'
[2026-07-11 00:56:50,927] [INFO ] Excluded 7 cells from groups: Plasma cell
[2026-07-11 00:56:50,934] [INFO ] Applying gene-wise z-scoring (standard_scale='var')
[2026-07-11 00:56:50,999] [WARNING ] standard_scale is ignored in fold_change_mode as z-scoring is not appropriate for fold changes
Fold-change dotplot¶
The same summary with a second dimension: color = mean log fold change, dot size = fraction of cells expressing (`dotplot <https://kompot.readthedocs.io/en/latest/plotting.html#kompot.plot.dotplot>`__):
[12]:
categories = [c for c in adata.obs[CELL_TYPE_COLUMN].cat.categories if c != "Plasma cell"]
kompot.plot.dotplot(
adata,
genes=None, # auto-pick top genes by Mahalanobis
groupby=CELL_TYPE_COLUMN,
categories_order=categories,
n_top=15,
)
[2026-07-11 00:56:52,176] [INFO ] Found DE run info for run_id=-1
[2026-07-11 00:56:52,177] [INFO ] Found mahalanobis_key='kompot_de_Young_to_Old_mahalanobis' from run info
[2026-07-11 00:56:52,178] [INFO ] Successfully inferred fields: {'mahalanobis_key': 'kompot_de_Young_to_Old_mahalanobis'}
[2026-07-11 00:56:52,179] [INFO ] Using DE run 0 for heatmap.
[2026-07-11 00:56:52,179] [INFO ] Inferred score_key='kompot_de_Young_to_Old_mahalanobis' from run information
[2026-07-11 00:56:52,184] [INFO ] Using expression data from layer: 'kompot_de_Young_to_Old_fold_change'
[2026-07-11 00:56:52,203] [INFO ] Using expression data from adata.X
Functional enrichment¶
Send the significant genes to the STRING database and summarize enriched processes.
Privacy note: this sends the gene list to an external API. For sensitive data, use a local enrichment tool instead.
[13]:
sig_genes = adata.var_names[adata.var[f"kompot_de_{c1}_to_{c2}_is_de"]]
report = kompot.plot.StringDBReport(
sig_genes,
species_id=10090, # 10090 = Mus musculus, 9606 = Homo sapiens
include_enrichment=True,
background=adata.var_names, # test against measured genes, not the whole genome
)
report
[2026-07-11 00:57:09,404] [WARNING ] 2500 of 16285 identifiers could not be mapped to STRING IDs (e.g. 4732440D04Rik, Gm26901, 2610203C22Rik, 1700034P13Rik, Snhg6); they are excluded from the enrichment universe.
[2026-07-11 00:57:10,555] [WARNING ] 10 of 192 identifiers could not be mapped to STRING IDs (e.g. Trbc2, Igkc, Kcnq1ot1, Ighd, Ighm); they are excluded from the enrichment universe.
[13]:
Gene Set Report: 192 genes
Species: Mus musculus (Taxonomy ID: 10090)
StringDB Network
View interactive network in StringDB
Resource Links (192 genes)
Functional Enrichment Analysis
View interactive enrichment analysis on StringDB
Gene Ontology Processes (513 terms)
| term | description | signal | strength | fdr | number_of_genes | inputGenes |
|---|---|---|---|---|---|---|
| GO:0002774 | Fc receptor mediated inhibitory signaling pathway | 0.433774 | 1.856106 | 1.700000e-03 | 3 | [10090.ENSMUSP00000038838, 10090.ENSMUSP00000077833, 10090.ENSMUSP00000099958] |
| GO:0060337 | Type I interferon signaling pathway | 0.379033 | 1.378984 | 4.050000e-05 | 6 | [10090.ENSMUSP00000026565, 10090.ENSMUSP00000071470, 10090.ENSMUSP00000082142, 10090.ENSMUSP00000101657, 10090.ENSMUSP00000141132, 10090.ENSMUSP00000147357] |
| GO:0002476 | Antigen processing and presentation of endogenous peptide antigen via MHC class Ib | 0.362382 | 1.408948 | 2.100000e-04 | 5 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000134550] |
| GO:0002483 | Antigen processing and presentation of endogenous peptide antigen | 0.350459 | 1.333227 | 6.120000e-05 | 6 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000128401, 10090.ENSMUSP00000134550] |
| GO:0048002 | Antigen processing and presentation of peptide antigen | 0.320524 | 1.173222 | 9.240000e-08 | 11 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078875, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000095171, 10090.ENSMUSP00000128401, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000158533] |
| GO:0045588 | Positive regulation of gamma-delta T cell differentiation | 0.319795 | 1.416773 | 1.400000e-03 | 4 | [10090.ENSMUSP00000056820, 10090.ENSMUSP00000113852, 10090.ENSMUSP00000125777, 10090.ENSMUSP00000145211] |
| GO:0002669 | Positive regulation of T cell anergy | 0.309065 | 1.555076 | 5.800000e-03 | 3 | [10090.ENSMUSP00000077833, 10090.ENSMUSP00000099896, 10090.ENSMUSP00000099958] |
| GO:0033634 | Positive regulation of cell-cell adhesion mediated by integrin | 0.309065 | 1.555076 | 5.800000e-03 | 3 | [10090.ENSMUSP00000039600, 10090.ENSMUSP00000057983, 10090.ENSMUSP00000099896] |
| GO:0002478 | Antigen processing and presentation of exogenous peptide antigen | 0.306283 | 1.224082 | 3.500000e-05 | 7 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000078875, 10090.ENSMUSP00000095171, 10090.ENSMUSP00000128401, 10090.ENSMUSP00000158533] |
| GO:0019886 | Antigen processing and presentation of exogenous peptide antigen via MHC class II | 0.302427 | 1.299803 | 4.800000e-04 | 5 | [10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000078875, 10090.ENSMUSP00000095171, 10090.ENSMUSP00000158533] |
| GO:0045059 | Positive thymic T cell selection | 0.301053 | 1.378984 | 1.800000e-03 | 4 | [10090.ENSMUSP00000002101, 10090.ENSMUSP00000034602, 10090.ENSMUSP00000095171, 10090.ENSMUSP00000099896] |
| GO:0050853 | B cell receptor signaling pathway | 0.288775 | 1.168131 | 1.330000e-05 | 8 | [10090.ENSMUSP00000003469, 10090.ENSMUSP00000038838, 10090.ENSMUSP00000100464, 10090.ENSMUSP00000113852, 10090.ENSMUSP00000125777, 10090.ENSMUSP00000126422, 10090.ENSMUSP00000129029, 10090.ENSMUSP00000143401] |
| GO:0045730 | Respiratory burst | 0.284076 | 1.344222 | 2.300000e-03 | 4 | [10090.ENSMUSP00000015484, 10090.ENSMUSP00000016094, 10090.ENSMUSP00000057983, 10090.ENSMUSP00000140404] |
| GO:0110089 | Regulation of hippocampal neuron apoptotic process | 0.282093 | 1.488129 | 7.900000e-03 | 3 | [10090.ENSMUSP00000032800, 10090.ENSMUSP00000053962, 10090.ENSMUSP00000068468] |
| GO:0031394 | Positive regulation of prostaglandin biosynthetic process | 0.282093 | 1.488129 | 7.900000e-03 | 3 | [10090.ENSMUSP00000025561, 10090.ENSMUSP00000028881, 10090.ENSMUSP00000095171] |
| GO:0035821 | Modulation of process of another organism | 0.279197 | 1.254046 | 6.900000e-04 | 5 | [10090.ENSMUSP00000035077, 10090.ENSMUSP00000104992, 10090.ENSMUSP00000107653, 10090.ENSMUSP00000112843, 10090.ENSMUSP00000113852] |
| GO:0034118 | Regulation of erythrocyte aggregation | 0.277734 | 1.856106 | 2.440000e-02 | 2 | [10090.ENSMUSP00000057983, 10090.ENSMUSP00000086795] |
| GO:0045584 | Negative regulation of cytotoxic T cell differentiation | 0.277734 | 1.856106 | 2.440000e-02 | 2 | [10090.ENSMUSP00000077833, 10090.ENSMUSP00000099958] |
| GO:0110090 | Positive regulation of hippocampal neuron apoptotic process | 0.277734 | 1.856106 | 2.440000e-02 | 2 | [10090.ENSMUSP00000032800, 10090.ENSMUSP00000068468] |
| GO:0070488 | Neutrophil aggregation | 0.277734 | 1.856106 | 2.440000e-02 | 2 | [10090.ENSMUSP00000064385, 10090.ENSMUSP00000112843] |
Showing 20 of 513 enriched terms
KEGG Pathways (43 terms)
| term | description | signal | strength | fdr | number_of_genes | inputGenes |
|---|---|---|---|---|---|---|
| mmu05332 | Graft-versus-host disease | 0.883180 | 1.254046 | 2.910000e-07 | 9 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000028881, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000158533] |
| mmu04940 | Type I diabetes mellitus | 0.844041 | 1.219283 | 3.750000e-07 | 9 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000028881, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000158533] |
| mmu04640 | Hematopoietic cell lineage | 0.817518 | 1.093749 | 5.430000e-09 | 14 | [10090.ENSMUSP00000002101, 10090.ENSMUSP00000028881, 10090.ENSMUSP00000029456, 10090.ENSMUSP00000032492, 10090.ENSMUSP00000033063, 10090.ENSMUSP00000034602, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000057983, 10090.ENSMUSP00000068468, 10090.ENSMUSP00000070131, 10090.ENSMUSP00000099896, 10090.ENSMUSP00000126422, 10090.ENSMUSP00000158533] |
| mmu05320 | Autoimmune thyroid disease | 0.776443 | 1.202893 | 2.010000e-06 | 8 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000158533] |
| mmu05330 | Allograft rejection | 0.776443 | 1.202893 | 2.010000e-06 | 8 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000158533] |
| mmu05140 | Leishmaniasis | 0.766941 | 1.112168 | 1.710000e-07 | 11 | [10090.ENSMUSP00000015484, 10090.ENSMUSP00000016094, 10090.ENSMUSP00000021674, 10090.ENSMUSP00000028881, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000068468, 10090.ENSMUSP00000102711, 10090.ENSMUSP00000140404, 10090.ENSMUSP00000141132, 10090.ENSMUSP00000158533] |
| mmu04612 | Antigen processing and presentation | 0.766941 | 1.112168 | 1.710000e-07 | 11 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000070131, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000095171, 10090.ENSMUSP00000128401, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000158533] |
| mmu05323 | Rheumatoid arthritis | 0.655180 | 1.036562 | 1.280000e-06 | 10 | [10090.ENSMUSP00000021674, 10090.ENSMUSP00000022921, 10090.ENSMUSP00000025262, 10090.ENSMUSP00000028881, 10090.ENSMUSP00000039600, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000074885, 10090.ENSMUSP00000102711, 10090.ENSMUSP00000158533] |
| mmu04658 | Th1 and Th2 cell differentiation | 0.630494 | 0.994408 | 7.860000e-07 | 11 | [10090.ENSMUSP00000002101, 10090.ENSMUSP00000021674, 10090.ENSMUSP00000032997, 10090.ENSMUSP00000034602, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000099896, 10090.ENSMUSP00000102711, 10090.ENSMUSP00000125777, 10090.ENSMUSP00000141132, 10090.ENSMUSP00000158533] |
| mmu04659 | Th17 cell differentiation | 0.628525 | 0.976245 | 3.750000e-07 | 12 | [10090.ENSMUSP00000002101, 10090.ENSMUSP00000021674, 10090.ENSMUSP00000028881, 10090.ENSMUSP00000032997, 10090.ENSMUSP00000034602, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000099896, 10090.ENSMUSP00000102711, 10090.ENSMUSP00000125777, 10090.ENSMUSP00000141132, 10090.ENSMUSP00000158533] |
| mmu05169 | Epstein-Barr virus infection | 0.586873 | 0.872408 | 5.430000e-09 | 19 | [10090.ENSMUSP00000000188, 10090.ENSMUSP00000002101, 10090.ENSMUSP00000025181, 10090.ENSMUSP00000028062, 10090.ENSMUSP00000034602, 10090.ENSMUSP00000034740, 10090.ENSMUSP00000038838, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000099896, 10090.ENSMUSP00000102711, 10090.ENSMUSP00000113852, 10090.ENSMUSP00000128401, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000141132, 10090.ENSMUSP00000158533] |
| mmu04514 | Cell adhesion molecules | 0.584653 | 0.924726 | 3.750000e-07 | 13 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000027871, 10090.ENSMUSP00000029456, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000068468, 10090.ENSMUSP00000070131, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000098436, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000158533] |
| mmu05416 | Viral myocarditis | 0.583991 | 1.034920 | 2.120000e-05 | 8 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000158533] |
| mmu04380 | Osteoclast differentiation | 0.581384 | 0.920831 | 3.750000e-07 | 13 | [10090.ENSMUSP00000003640, 10090.ENSMUSP00000016094, 10090.ENSMUSP00000021674, 10090.ENSMUSP00000028881, 10090.ENSMUSP00000032800, 10090.ENSMUSP00000064680, 10090.ENSMUSP00000077833, 10090.ENSMUSP00000092901, 10090.ENSMUSP00000102711, 10090.ENSMUSP00000113852, 10090.ENSMUSP00000125777, 10090.ENSMUSP00000140404, 10090.ENSMUSP00000141132] |
| mmu04657 | IL-17 signaling pathway | 0.571185 | 0.990804 | 1.110000e-05 | 9 | [10090.ENSMUSP00000003640, 10090.ENSMUSP00000021674, 10090.ENSMUSP00000028881, 10090.ENSMUSP00000053962, 10090.ENSMUSP00000064385, 10090.ENSMUSP00000074885, 10090.ENSMUSP00000092901, 10090.ENSMUSP00000102711, 10090.ENSMUSP00000112843] |
| mmu05340 | Primary immunodeficiency | 0.528634 | 1.077954 | 2.400000e-04 | 6 | [10090.ENSMUSP00000003469, 10090.ENSMUSP00000034602, 10090.ENSMUSP00000070131, 10090.ENSMUSP00000099896, 10090.ENSMUSP00000125777, 10090.ENSMUSP00000128401] |
| mmu04145 | Phagosome | 0.528032 | 0.869678 | 8.770000e-07 | 13 | [10090.ENSMUSP00000015484, 10090.ENSMUSP00000016094, 10090.ENSMUSP00000025181, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000068468, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000128401, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000140404, 10090.ENSMUSP00000158533] |
| mmu04662 | B cell receptor signaling pathway | 0.526837 | 0.947025 | 2.120000e-05 | 9 | [10090.ENSMUSP00000003469, 10090.ENSMUSP00000021674, 10090.ENSMUSP00000038838, 10090.ENSMUSP00000043768, 10090.ENSMUSP00000077833, 10090.ENSMUSP00000101657, 10090.ENSMUSP00000102711, 10090.ENSMUSP00000113852, 10090.ENSMUSP00000129029] |
| mmu05150 | Staphylococcus aureus infection | 0.510241 | 1.054473 | 2.900000e-04 | 6 | [10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000068468, 10090.ENSMUSP00000098436, 10090.ENSMUSP00000107653, 10090.ENSMUSP00000158533] |
| mmu05166 | Human T-cell leukemia virus 1 infection | 0.501021 | 0.801748 | 7.340000e-08 | 18 | [10090.ENSMUSP00000000188, 10090.ENSMUSP00000002101, 10090.ENSMUSP00000021674, 10090.ENSMUSP00000025181, 10090.ENSMUSP00000034534, 10090.ENSMUSP00000034602, 10090.ENSMUSP00000037039, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000057815, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000099896, 10090.ENSMUSP00000102711, 10090.ENSMUSP00000125777, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000158533] |
Showing 20 of 43 enriched terms
Gene Ontology Functions (29 terms)
| term | description | signal | strength | fdr | number_of_genes | inputGenes |
|---|---|---|---|---|---|---|
| GO:0042605 | Peptide antigen binding | 0.882353 | 1.531594 | 1.530000e-07 | 9 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000128401, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000158533] |
| GO:0042610 | CD8 receptor binding | 0.695797 | 1.520313 | 4.690000e-05 | 6 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000125777, 10090.ENSMUSP00000134550] |
| GO:0046979 | TAP2 binding | 0.667945 | 1.488129 | 5.310000e-05 | 6 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000128401, 10090.ENSMUSP00000134550] |
| GO:0046978 | TAP1 binding | 0.639822 | 1.458166 | 6.430000e-05 | 6 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000128401, 10090.ENSMUSP00000134550] |
| GO:0042608 | T cell receptor binding | 0.630797 | 1.400174 | 2.090000e-05 | 7 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000125777, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000158533] |
| GO:0003823 | Antigen binding | 0.576727 | 1.244286 | 1.880000e-07 | 11 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000100464, 10090.ENSMUSP00000125777, 10090.ENSMUSP00000128401, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000158533] |
| GO:0030881 | beta-2-microglobulin binding | 0.523778 | 1.408948 | 6.500000e-04 | 5 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000134550] |
| GO:0042287 | MHC protein binding | 0.509045 | 1.219283 | 7.440000e-06 | 9 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000043768, 10090.ENSMUSP00000070131, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000095171, 10090.ENSMUSP00000128401, 10090.ENSMUSP00000134550] |
| GO:0042288 | MHC class I protein binding | 0.465867 | 1.224082 | 1.100000e-04 | 7 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000070131, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000128401, 10090.ENSMUSP00000134550] |
| GO:0046703 | Natural killer cell lectin-like receptor binding | 0.435007 | 1.299803 | 1.600000e-03 | 5 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000134550] |
| GO:0016175 | Superoxide-generating NAD(P)H oxidase activity | 0.431722 | 1.634257 | 1.330000e-02 | 3 | [10090.ENSMUSP00000015484, 10090.ENSMUSP00000016094, 10090.ENSMUSP00000140404] |
| GO:0023026 | MHC class II protein complex binding | 0.412608 | 1.378984 | 5.800000e-03 | 4 | [10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000095171, 10090.ENSMUSP00000158533] |
| GO:0030547 | Signaling receptor inhibitor activity | 0.385379 | 1.232856 | 2.800000e-03 | 5 | [10090.ENSMUSP00000039600, 10090.ENSMUSP00000077833, 10090.ENSMUSP00000098110, 10090.ENSMUSP00000099958, 10090.ENSMUSP00000140287] |
| GO:0071889 | 14-3-3 protein binding | 0.350228 | 1.077954 | 5.900000e-04 | 7 | [10090.ENSMUSP00000021552, 10090.ENSMUSP00000025181, 10090.ENSMUSP00000057815, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000134550] |
| GO:0070492 | Oligosaccharide binding | 0.295634 | 1.378984 | 4.240000e-02 | 3 | [10090.ENSMUSP00000027871, 10090.ENSMUSP00000086795, 10090.ENSMUSP00000118169] |
| GO:0016209 | Antioxidant activity | 0.287000 | 0.953016 | 7.200000e-04 | 8 | [10090.ENSMUSP00000033992, 10090.ENSMUSP00000064385, 10090.ENSMUSP00000071130, 10090.ENSMUSP00000074436, 10090.ENSMUSP00000081010, 10090.ENSMUSP00000112843, 10090.ENSMUSP00000112923, 10090.ENSMUSP00000133302] |
| GO:0042277 | Peptide binding | 0.195709 | 0.698498 | 5.310000e-05 | 16 | [10090.ENSMUSP00000005671, 10090.ENSMUSP00000025181, 10090.ENSMUSP00000033992, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000058613, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000095171, 10090.ENSMUSP00000095253, 10090.ENSMUSP00000112923, 10090.ENSMUSP00000128401, 10090.ENSMUSP00000133302, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000158533] |
| GO:0033218 | Amide binding | 0.161035 | 0.609433 | 1.900000e-04 | 17 | [10090.ENSMUSP00000005671, 10090.ENSMUSP00000025181, 10090.ENSMUSP00000033992, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000058613, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000095171, 10090.ENSMUSP00000095253, 10090.ENSMUSP00000110440, 10090.ENSMUSP00000112923, 10090.ENSMUSP00000128401, 10090.ENSMUSP00000133302, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000158533] |
| GO:0030545 | Signaling receptor regulator activity | 0.144578 | 0.591651 | 3.700000e-03 | 13 | [10090.ENSMUSP00000025262, 10090.ENSMUSP00000028881, 10090.ENSMUSP00000035009, 10090.ENSMUSP00000039600, 10090.ENSMUSP00000063627, 10090.ENSMUSP00000065940, 10090.ENSMUSP00000070238, 10090.ENSMUSP00000074885, 10090.ENSMUSP00000077833, 10090.ENSMUSP00000098110, 10090.ENSMUSP00000099958, 10090.ENSMUSP00000118169, 10090.ENSMUSP00000140287] |
| GO:1901681 | Sulfur compound binding | 0.130888 | 0.591288 | 2.470000e-02 | 10 | [10090.ENSMUSP00000022529, 10090.ENSMUSP00000033992, 10090.ENSMUSP00000034282, 10090.ENSMUSP00000035077, 10090.ENSMUSP00000039600, 10090.ENSMUSP00000068468, 10090.ENSMUSP00000101980, 10090.ENSMUSP00000112923, 10090.ENSMUSP00000133302, 10090.ENSMUSP00000137520] |
Showing 20 of 29 enriched terms
Gene Ontology Components (46 terms)
| term | description | signal | strength | fdr | number_of_genes | inputGenes |
|---|---|---|---|---|---|---|
| GO:0042611 | MHC protein complex | 0.510178 | 1.448620 | 4.700000e-08 | 9 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000095171, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000158533] |
| GO:0035976 | Transcription factor AP-1 complex | 0.476990 | 1.759196 | 4.000000e-04 | 4 | [10090.ENSMUSP00000021674, 10090.ENSMUSP00000064680, 10090.ENSMUSP00000092901, 10090.ENSMUSP00000102711] |
| GO:0019815 | B cell receptor complex | 0.404799 | 1.856106 | 2.900000e-03 | 3 | [10090.ENSMUSP00000003469, 10090.ENSMUSP00000113852, 10090.ENSMUSP00000129029] |
| GO:0019814 | Immunoglobulin complex | 0.403079 | 1.613067 | 7.700000e-04 | 4 | [10090.ENSMUSP00000003469, 10090.ENSMUSP00000100464, 10090.ENSMUSP00000113852, 10090.ENSMUSP00000129029] |
| GO:0032398 | MHC class Ib protein complex | 0.403015 | 1.513683 | 2.400000e-04 | 5 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000134550] |
| GO:0042612 | MHC class I protein complex | 0.364062 | 1.441132 | 3.500000e-04 | 5 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000134550] |
| GO:0042105 | Alpha-beta T cell receptor complex | 0.319853 | 1.634257 | 6.600000e-03 | 3 | [10090.ENSMUSP00000002101, 10090.ENSMUSP00000034602, 10090.ENSMUSP00000099896] |
| GO:0033106 | cis-Golgi network membrane | 0.317981 | 1.350956 | 5.800000e-04 | 5 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000134550] |
| GO:0042613 | MHC class II protein complex | 0.304548 | 1.416773 | 2.400000e-03 | 4 | [10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000095171, 10090.ENSMUSP00000158533] |
| GO:0042101 | T cell receptor complex | 0.256551 | 1.312037 | 4.700000e-03 | 4 | [10090.ENSMUSP00000002101, 10090.ENSMUSP00000034602, 10090.ENSMUSP00000099896, 10090.ENSMUSP00000113852] |
| GO:0043020 | NADPH oxidase complex | 0.243366 | 1.430137 | 1.580000e-02 | 3 | [10090.ENSMUSP00000015484, 10090.ENSMUSP00000016094, 10090.ENSMUSP00000140404] |
| GO:0001772 | Immunological synapse | 0.212011 | 1.047991 | 4.700000e-04 | 7 | [10090.ENSMUSP00000032997, 10090.ENSMUSP00000033063, 10090.ENSMUSP00000043768, 10090.ENSMUSP00000099896, 10090.ENSMUSP00000118169, 10090.ENSMUSP00000125777, 10090.ENSMUSP00000158533] |
| GO:0042824 | MHC class I peptide loading complex | 0.194968 | 1.291834 | 3.040000e-02 | 3 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000128401, 10090.ENSMUSP00000134550] |
| GO:0071556 | Integral component of lumenal side of endoplasmic reticulum membrane | 0.167261 | 1.187099 | 4.250000e-02 | 3 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000134550] |
| GO:0009897 | External side of plasma membrane | 0.154242 | 0.778132 | 2.510000e-12 | 30 | [10090.ENSMUSP00000002101, 10090.ENSMUSP00000003469, 10090.ENSMUSP00000025181, 10090.ENSMUSP00000025561, 10090.ENSMUSP00000027871, 10090.ENSMUSP00000029456, 10090.ENSMUSP00000032492, 10090.ENSMUSP00000033992, 10090.ENSMUSP00000034602, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000048303, 10090.ENSMUSP00000057983, 10090.ENSMUSP00000068468, 10090.ENSMUSP00000070131, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000077833, 10090.ENSMUSP00000078875, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000095171, 10090.ENSMUSP00000099896, 10090.ENSMUSP00000100464, 10090.ENSMUSP00000118169, 10090.ENSMUSP00000126422, 10090.ENSMUSP00000129029, 10090.ENSMUSP00000133302, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000140287, 10090.ENSMUSP00000158533] |
| GO:0001533 | Cornified envelope | 0.146818 | 1.011008 | 3.090000e-02 | 4 | [10090.ENSMUSP00000025561, 10090.ENSMUSP00000034756, 10090.ENSMUSP00000112843, 10090.ENSMUSP00000118169] |
| GO:0005771 | Multivesicular body | 0.144036 | 0.893894 | 7.600000e-03 | 6 | [10090.ENSMUSP00000003469, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000056820, 10090.ENSMUSP00000058613, 10090.ENSMUSP00000095171, 10090.ENSMUSP00000151313] |
| GO:0098797 | Plasma membrane protein complex | 0.128815 | 0.699370 | 3.350000e-09 | 26 | [10090.ENSMUSP00000002101, 10090.ENSMUSP00000003469, 10090.ENSMUSP00000005671, 10090.ENSMUSP00000015484, 10090.ENSMUSP00000016094, 10090.ENSMUSP00000025181, 10090.ENSMUSP00000031670, 10090.ENSMUSP00000034602, 10090.ENSMUSP00000034756, 10090.ENSMUSP00000038838, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000068468, 10090.ENSMUSP00000069495, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078875, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000095171, 10090.ENSMUSP00000095253, 10090.ENSMUSP00000099896, 10090.ENSMUSP00000113852, 10090.ENSMUSP00000129029, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000140404, 10090.ENSMUSP00000158533] |
| GO:0098552 | Side of membrane | 0.124352 | 0.677608 | 2.510000e-12 | 36 | [10090.ENSMUSP00000001051, 10090.ENSMUSP00000002101, 10090.ENSMUSP00000003469, 10090.ENSMUSP00000025181, 10090.ENSMUSP00000025561, 10090.ENSMUSP00000027871, 10090.ENSMUSP00000029456, 10090.ENSMUSP00000031670, 10090.ENSMUSP00000032492, 10090.ENSMUSP00000033992, 10090.ENSMUSP00000034602, 10090.ENSMUSP00000038838, 10090.ENSMUSP00000041008, 10090.ENSMUSP00000046105, 10090.ENSMUSP00000048303, 10090.ENSMUSP00000057983, 10090.ENSMUSP00000068468, 10090.ENSMUSP00000070131, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000077833, 10090.ENSMUSP00000078875, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000095171, 10090.ENSMUSP00000099896, 10090.ENSMUSP00000100464, 10090.ENSMUSP00000113852, 10090.ENSMUSP00000115558, 10090.ENSMUSP00000118169, 10090.ENSMUSP00000125777, 10090.ENSMUSP00000126422, 10090.ENSMUSP00000129029, 10090.ENSMUSP00000133302, 10090.ENSMUSP00000134550, 10090.ENSMUSP00000140287, 10090.ENSMUSP00000158533] |
| GO:0098802 | Plasma membrane signaling receptor complex | 0.115109 | 0.719385 | 1.900000e-03 | 10 | [10090.ENSMUSP00000002101, 10090.ENSMUSP00000003469, 10090.ENSMUSP00000005671, 10090.ENSMUSP00000034602, 10090.ENSMUSP00000038838, 10090.ENSMUSP00000068468, 10090.ENSMUSP00000095253, 10090.ENSMUSP00000099896, 10090.ENSMUSP00000113852, 10090.ENSMUSP00000129029] |
Showing 20 of 46 enriched terms
Reactome Pathways (33 terms)
| term | description | signal | strength | fdr | number_of_genes | inputGenes |
|---|---|---|---|---|---|---|
| MMU-6799990 | Metal sequestration by antimicrobial proteins | 0.524295 | 1.856106 | 2.800000e-04 | 4 | [10090.ENSMUSP00000035077, 10090.ENSMUSP00000053962, 10090.ENSMUSP00000064385, 10090.ENSMUSP00000112843] |
| MMU-202430 | Translocation of ZAP-70 to Immunological synapse | 0.429845 | 1.555076 | 1.700000e-04 | 5 | [10090.ENSMUSP00000002101, 10090.ENSMUSP00000034602, 10090.ENSMUSP00000099896, 10090.ENSMUSP00000125777, 10090.ENSMUSP00000158533] |
| MMU-202433 | Generation of second messenger molecules | 0.410490 | 1.400174 | 1.090000e-05 | 7 | [10090.ENSMUSP00000002101, 10090.ENSMUSP00000032997, 10090.ENSMUSP00000034602, 10090.ENSMUSP00000087947, 10090.ENSMUSP00000099896, 10090.ENSMUSP00000125777, 10090.ENSMUSP00000158533] |
| MMU-5690714 | CD22 mediated BCR regulation | 0.398608 | 1.613067 | 8.700000e-04 | 4 | [10090.ENSMUSP00000003469, 10090.ENSMUSP00000038838, 10090.ENSMUSP00000100464, 10090.ENSMUSP00000129029] |
| MMU-202427 | Phosphorylation of CD3 and TCR zeta chains | 0.363382 | 1.441132 | 3.600000e-04 | 5 | [10090.ENSMUSP00000002101, 10090.ENSMUSP00000034602, 10090.ENSMUSP00000099896, 10090.ENSMUSP00000125777, 10090.ENSMUSP00000158533] |
| MMU-389948 | PD-1 signaling | 0.346066 | 1.408948 | 4.400000e-04 | 5 | [10090.ENSMUSP00000002101, 10090.ENSMUSP00000034602, 10090.ENSMUSP00000099896, 10090.ENSMUSP00000125777, 10090.ENSMUSP00000158533] |
| MMU-6803157 | Antimicrobial peptides | 0.322933 | 1.269840 | 5.240000e-05 | 7 | [10090.ENSMUSP00000006679, 10090.ENSMUSP00000035077, 10090.ENSMUSP00000053962, 10090.ENSMUSP00000064385, 10090.ENSMUSP00000089801, 10090.ENSMUSP00000107653, 10090.ENSMUSP00000112843] |
| MMU-1236977 | Endosomal/Vacuolar pathway | 0.298921 | 1.416773 | 2.900000e-03 | 4 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159] |
| MMU-198933 | Immunoregulatory interactions between a Lymphoid and a non-Lymphoid cell | 0.291573 | 1.104606 | 6.020000e-09 | 14 | [10090.ENSMUSP00000002101, 10090.ENSMUSP00000025181, 10090.ENSMUSP00000026565, 10090.ENSMUSP00000027871, 10090.ENSMUSP00000034602, 10090.ENSMUSP00000043768, 10090.ENSMUSP00000070131, 10090.ENSMUSP00000071470, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000099896, 10090.ENSMUSP00000100464, 10090.ENSMUSP00000101657] |
| MMU-2871796 | FCERI mediated MAPK activation | 0.280823 | 1.196054 | 1.200000e-04 | 7 | [10090.ENSMUSP00000021674, 10090.ENSMUSP00000032997, 10090.ENSMUSP00000038838, 10090.ENSMUSP00000078875, 10090.ENSMUSP00000100464, 10090.ENSMUSP00000102711, 10090.ENSMUSP00000113852] |
| MMU-1236974 | ER-Phagosome pathway | 0.265210 | 1.254046 | 1.500000e-03 | 5 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000128401] |
| MMU-3299685 | Detoxification of Reactive Oxygen Species | 0.252429 | 1.171859 | 5.800000e-04 | 6 | [10090.ENSMUSP00000015484, 10090.ENSMUSP00000016094, 10090.ENSMUSP00000030051, 10090.ENSMUSP00000033992, 10090.ENSMUSP00000081010, 10090.ENSMUSP00000140404] |
| MMU-2029481 | FCGR activation | 0.241552 | 1.282074 | 6.200000e-03 | 4 | [10090.ENSMUSP00000002101, 10090.ENSMUSP00000038838, 10090.ENSMUSP00000100464, 10090.ENSMUSP00000113852] |
| MMU-1236973 | Cross-presentation of particulate exogenous antigens (phagosomes) | 0.237035 | 1.430137 | 1.850000e-02 | 3 | [10090.ENSMUSP00000015484, 10090.ENSMUSP00000016094, 10090.ENSMUSP00000140404] |
| MMU-5621480 | Dectin-2 family | 0.237035 | 1.430137 | 1.850000e-02 | 3 | [10090.ENSMUSP00000038838, 10090.ENSMUSP00000078875, 10090.ENSMUSP00000113852] |
| MMU-5668599 | RHO GTPases Activate NADPH Oxidases | 0.236880 | 1.193348 | 2.500000e-03 | 5 | [10090.ENSMUSP00000015484, 10090.ENSMUSP00000016094, 10090.ENSMUSP00000064385, 10090.ENSMUSP00000112843, 10090.ENSMUSP00000140404] |
| MMU-163754 | Insulin effects increased synthesis of Xylulose-5-Phosphate | 0.231900 | 1.856106 | 4.880000e-02 | 2 | [10090.ENSMUSP00000022529, 10090.ENSMUSP00000026576] |
| MMU-2730905 | Role of LAT2/NTAL/LAB on calcium mobilization | 0.219702 | 1.227717 | 8.700000e-03 | 4 | [10090.ENSMUSP00000038838, 10090.ENSMUSP00000078875, 10090.ENSMUSP00000100464, 10090.ENSMUSP00000113852] |
| MMU-983170 | Antigen Presentation: Folding, assembly and peptide loading of class I MHC | 0.207779 | 1.123712 | 4.300000e-03 | 5 | [10090.ENSMUSP00000025181, 10090.ENSMUSP00000071843, 10090.ENSMUSP00000078927, 10090.ENSMUSP00000080159, 10090.ENSMUSP00000128401] |
| MMU-2871809 | FCERI mediated Ca+2 mobilization | 0.196190 | 1.092678 | 5.300000e-03 | 5 | [10090.ENSMUSP00000032997, 10090.ENSMUSP00000038838, 10090.ENSMUSP00000078875, 10090.ENSMUSP00000100464, 10090.ENSMUSP00000113852] |
Showing 20 of 33 enriched terms
Turn the enriched terms into a compact lollipop plot (`lollipop <https://kompot.readthedocs.io/en/latest/plotting.html#kompot.plot.lollipop>`__):
[14]:
enrichment = report.get_functional_enrichment("Process")
kompot.plot.lollipop(enrichment, n_terms=12, title="Enriched biological processes")
Run history¶
Kompot records every run’s parameters and environment. Inspect the latest with `RunInfo <https://kompot.readthedocs.io/en/latest/anndata.html#kompot.anndata.utils.RunInfo>`__:
[15]:
kompot.RunInfo(adata, analysis_type="de")
[15]:
Run 0 (DE Analysis)
Run Summary
Analysis: DE | Run ID: 0 | Timestamp: 2026-07-11T00:56:48.400793 | Conditions: Young to OldAll Fields Present
| Parameter | Value |
|---|---|
| conditions | Young to Old |
| obsm_key | DM_EigenVectors |
| uses_sample_variance | False |
| layer | logged_counts |
| timestamp | 2026-07-11T00:56:48.400793 |
| Fields Created | 9 |
All Parameters
| Parameter | Value |
|---|---|
| groupby | Age |
| condition1 | Young |
| condition2 | Old |
| obsm_key | DM_EigenVectors |
| layer | logged_counts |
| gp | |
| gp.sigma | 1.0 |
| gp.ls_factor | 10.0 |
| gp.n_landmarks | 5000 |
| gp.use_empirical_variance | False |
| gp.batch_size | 0 |
| gp.eps | 1e-08 |
| gp.jit_compile | False |
| fdr | |
| fdr.null_genes | 2000 |
| fdr.null_seed | 42 |
| fdr.threshold | 0.05 |
| fdr.combine_with_internal | False |
| filter | |
| filter.min_cells | 2 |
| storage | |
| storage.result_key | kompot_de |
| storage.store_landmarks | False |
| storage.store_posterior_covariance | False |
| storage.store_additional_stats | False |
| storage.max_memory_ratio | 0.8 |
| output | |
| output.copy | False |
| output.inplace | True |
| output.return_full_results | False |
| output.return_null_data | False |
| output.compute_mahalanobis | True |
| output.allow_single_condition_variance | False |
| output.progress | True |
| result_key | kompot_de |
Environment
| Parameter | Value |
|---|---|
| hostname | gizmok87 |
| package_versions | anndata: 0.12.19 jax: 0.10.2 jaxlib: 0.10.2 kompot: 0.8.0 numpy: 2.4.6 pandas: 2.3.3 scipy: 1.17.1 |
| pid | 13995 |
| platform | Linux-5.4.0-228-generic-x86_64-with-glibc2.39 |
| python_version | 3.11.6 |
| timestamp | 2026-07-11T00:56:48.459886 |
| username | dotto |
Fields Created by This Run
Total Fields: 9 | Present: 9 | Missing: 0 | Overwritten: 0
| Field Name | Location | Description | Status |
|---|---|---|---|
| LAYERS Fields | |||
| kompot_de_Old_smoothed | layers | [smoothed] Imputed expression for Old | Present |
| kompot_de_Young_smoothed | layers | [smoothed] Imputed expression for Young | Present |
| kompot_de_Young_to_Old_fold_change | layers | [fold_change] Log fold change for each cell and gene | Present |
| OBS Fields | |||
| kompot_de_Old_std | obs | [std] Posterior standard deviation of smoothed expression for Old (same for all genes) | Present |
| kompot_de_Young_std | obs | [std] Posterior standard deviation of smoothed expression for Young (same for all genes) | Present |
| VAR Fields | |||
| kompot_de_Young_to_Old_is_de | var | [is_de] Boolean indicator of differential expression at local FDR < 0.05 | Present |
| kompot_de_Young_to_Old_mahalanobis | var | [mahalanobis] Mahalanobis distances | Present |
| kompot_de_Young_to_Old_mahalanobis_local_fdr | var | [mahalanobis_local_fdr] Local FDR values using empirical null estimation similar to R's fdrtool | Present |
| kompot_de_Young_to_Old_mean_lfc | var | [mean_log_fold_change] Mean log fold change values | Present |
Save¶
Smoothed-expression layers are large; `cleanup <https://kompot.readthedocs.io/en/latest/anndata.html#kompot.cleanup>`__ drops them while keeping the statistics in adata.var:
[16]:
kompot.cleanup(adata)
adata.write_h5ad("../data/murine_bone_marrow_aging_processed.h5ad")
[2026-07-11 00:57:54,254] [INFO ] Cleaning up all 1 run(s)
[2026-07-11 00:57:54,436] [INFO ] Cleaned up 3 field(s) from run 0:
[2026-07-11 00:57:54,436] [INFO ] layers (3 field(s)):
[2026-07-11 00:57:54,437] [INFO ] - kompot_de_Young_smoothed
[2026-07-11 00:57:54,437] [INFO ] - kompot_de_Old_smoothed
[2026-07-11 00:57:54,438] [INFO ] - kompot_de_Young_to_Old_fold_change
[2026-07-11 00:57:54,438] [INFO ] Total: Cleaned up 3 field(s) across 1 run(s)
Where to go deeper¶
Smoothing expression functions — the GP estimator underneath DE: length scales, uncertainty, and training on a subset to transfer modalities or build counterfactuals.
Advanced DE options — tuning (including
ls_factor, which controls how smooth the expression function is), multiple comparisons, run tracking, resource planning.DE with sample variance — robust significance when you have biological replicates.
Differential abundance — find cell states that change in frequency.
Paper — the full method and derivation.
Documentation — complete API reference.