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scArches+scANVI (Seurat v3 2000 HVG)

scArches+scANVI or "Single-cell architecture surgery" is a deep learning method for mapping new datasets onto a pre-existing reference model, using transfer learning and parameter optimization. It first uses scANVI to build a reference model from the training data, and then apply scArches to map the test data onto the reference model and make predictions.

24 evaluations · 24 metric rows

Overview

scArches+scANVI or "Single-cell architecture surgery" is a deep learning method for mapping new datasets onto a pre-existing reference model, using transfer learning and parameter optimization. It first uses scANVI to build a reference model from the training data, and then apply scArches to map the test data onto the reference model and make predictions.

Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.

Evaluations and results

Release 2026-09-17-134cd1815de8 · 24 evaluations · 24 metric rows. Different protocols are not a single leaderboard. Where several source tables report the same metric, the published comparisons above offer a pooled view that names what it does not hold constant.

Results grouped by the exact reported evaluation
Metric and findingCoverage and uncertaintyEvidence
scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection CENGEN-BATCH-ACCURACY: Label projection on CeNGEN (split by batch), Accuracy

100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.08028759736369083 accuracy

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(accuracy)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection CENGEN-BATCH-F1: Label projection on CeNGEN (split by batch), F1 score

100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.03725296782270025 f1

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(f1)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection CENGEN-BATCH-F1-MACRO: Label projection on CeNGEN (split by batch), Macro F1 score

100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test by experimental batch. Dimensions: 100955 cells, 22469 genes. 169 cell types (avg. 597±800 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.036846248365176415 f1-macro

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_batch), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(f1_macro)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection CENGEN-RANDOM-ACCURACY: Label projection on CeNGEN (random split), Accuracy

100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test randomly. Dimensions: 100955 cells, 22469 genes. 169 cell types avg. 597±800 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.34884870046447275 accuracy

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_random), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(accuracy)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection CENGEN-RANDOM-F1: Label projection on CeNGEN (random split), F1 score

100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test randomly. Dimensions: 100955 cells, 22469 genes. 169 cell types avg. 597±800 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.21567196436308758 f1

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_random), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(f1)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection CENGEN-RANDOM-F1-MACRO: Label projection on CeNGEN (random split), Macro F1 score

100k FACS-isolated C. elegans neurons from 17 experiments sequenced on 10x Genomics. Split into train/test randomly. Dimensions: 100955 cells, 22469 genes. 169 cell types avg. 597±800 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.04927592126738169 f1-macro

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(cengen_random), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(f1_macro)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection PANCREAS-BATCH-ACCURACY: Label projection on Pancreas (by batch), Accuracy

Human pancreatic islet scRNA-seq data from 6 datasets across technologies (CEL-seq, CEL-seq2, Smart-seq2, inDrop, Fluidigm C1, and SMARTER-seq). Split into train/test by experimental batch. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.9540167703543414 accuracy

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(pancreas_batch), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(accuracy)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection PANCREAS-BATCH-F1: Label projection on Pancreas (by batch), F1 score

Human pancreatic islet scRNA-seq data from 6 datasets across technologies (CEL-seq, CEL-seq2, Smart-seq2, inDrop, Fluidigm C1, and SMARTER-seq). Split into train/test by experimental batch. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.9517252686049228 f1

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(pancreas_batch), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(f1)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection PANCREAS-BATCH-F1-MACRO: Label projection on Pancreas (by batch), Macro F1 score

Human pancreatic islet scRNA-seq data from 6 datasets across technologies (CEL-seq, CEL-seq2, Smart-seq2, inDrop, Fluidigm C1, and SMARTER-seq). Split into train/test by experimental batch. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.5816215781285415 f1-macro

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(pancreas_batch), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(f1_macro)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection PANCREAS-RANDOM-ACCURACY: Label projection on Pancreas (random split), Accuracy

Human pancreatic islet scRNA-seq data from 6 datasets across technologies (CEL-seq, CEL-seq2, Smart-seq2, inDrop, Fluidigm C1, and SMARTER-seq). Split into train/test randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.956838905775076 accuracy

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(accuracy)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection PANCREAS-RANDOM-F1: Label projection on Pancreas (random split), F1 score

Human pancreatic islet scRNA-seq data from 6 datasets across technologies (CEL-seq, CEL-seq2, Smart-seq2, inDrop, Fluidigm C1, and SMARTER-seq). Split into train/test randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.9478276041369139 f1

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(f1)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection PANCREAS-RANDOM-F1-MACRO: Label projection on Pancreas (random split), Macro F1 score

Human pancreatic islet scRNA-seq data from 6 datasets across technologies (CEL-seq, CEL-seq2, Smart-seq2, inDrop, Fluidigm C1, and SMARTER-seq). Split into train/test randomly. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.529456773064677 f1-macro

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(pancreas_random), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(f1_macro)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection PANCREAS-RANDOM-LABEL-NOISE-ACCURACY: Label projection on Pancreas (random split with label noise), Accuracy

Human pancreatic islet scRNA-seq data from 6 datasets across technologies (CEL-seq, CEL-seq2, Smart-seq2, inDrop, Fluidigm C1, and SMARTER-seq). Split into train/test randomly with 20% label noise. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.9476117103235747 accuracy

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(pancreas_random_label_noise), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(accuracy)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection PANCREAS-RANDOM-LABEL-NOISE-F1: Label projection on Pancreas (random split with label noise), F1 score

Human pancreatic islet scRNA-seq data from 6 datasets across technologies (CEL-seq, CEL-seq2, Smart-seq2, inDrop, Fluidigm C1, and SMARTER-seq). Split into train/test randomly with 20% label noise. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.9372298848234738 f1

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(pancreas_random_label_noise), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(f1)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection PANCREAS-RANDOM-LABEL-NOISE-F1-MACRO: Label projection on Pancreas (random split with label noise), Macro F1 score

Human pancreatic islet scRNA-seq data from 6 datasets across technologies (CEL-seq, CEL-seq2, Smart-seq2, inDrop, Fluidigm C1, and SMARTER-seq). Split into train/test randomly with 20% label noise. Dimensions: 16382 cells, 18771 genes. 14 cell types (avg. 1170±1703 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.527328944140918 f1-macro

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(pancreas_random_label_noise), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(f1_macro)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-ACCURACY: Label projection on Tabula Muris Senis Lung (random split), Accuracy

All lung cells from Tabula Muris Senis, a 500k cell-atlas from 18 organs and tissues across the mouse lifespan. Split into train/test randomly. Dimensions: 24540 cells, 17985 genes. 39 cell types (avg. 629±999 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.7223671013039117 accuracy

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(accuracy)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-F1: Label projection on Tabula Muris Senis Lung (random split), F1 score

All lung cells from Tabula Muris Senis, a 500k cell-atlas from 18 organs and tissues across the mouse lifespan. Split into train/test randomly. Dimensions: 24540 cells, 17985 genes. 39 cell types (avg. 629±999 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.6280996816595446 f1

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(f1)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection TABULA-MURIS-SENIS-LUNG-RANDOM-F1-MACRO: Label projection on Tabula Muris Senis Lung (random split), Macro F1 score

All lung cells from Tabula Muris Senis, a 500k cell-atlas from 18 organs and tissues across the mouse lifespan. Split into train/test randomly. Dimensions: 24540 cells, 17985 genes. 39 cell types (avg. 629±999 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.23443165472180164 f1-macro

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(tabula_muris_senis_lung_random), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(f1_macro)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection ZEBRAFISH-LABS-ACCURACY: Label projection on Zebrafish (by laboratory), Accuracy

90k cells from zebrafish embryos throughout the first day of development, with and without a knockout of chordin, an important developmental gene. Split into train/test by laboratory. Dimensions: 26022 cells, 25258 genes. 24 cell types (avg. 1084±1156 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.13280134942260283 accuracy

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(zebrafish_labs), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(accuracy)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection ZEBRAFISH-LABS-F1: Label projection on Zebrafish (by laboratory), F1 score

90k cells from zebrafish embryos throughout the first day of development, with and without a knockout of chordin, an important developmental gene. Split into train/test by laboratory. Dimensions: 26022 cells, 25258 genes. 24 cell types (avg. 1084±1156 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.1309776775288379 f1

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(zebrafish_labs), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(f1)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection ZEBRAFISH-LABS-F1-MACRO: Label projection on Zebrafish (by laboratory), Macro F1 score

90k cells from zebrafish embryos throughout the first day of development, with and without a knockout of chordin, an important developmental gene. Split into train/test by laboratory. Dimensions: 26022 cells, 25258 genes. 24 cell types (avg. 1084±1156 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.21771900557535676 f1-macro

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(zebrafish_labs), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(f1_macro)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection ZEBRAFISH-RANDOM-ACCURACY: Label projection on Zebrafish (random split), Accuracy

90k cells from zebrafish embryos throughout the first day of development, with and without a knockout of chordin, an important developmental gene. Split into train/test randomly. Dimensions: 26022 cells, 25258 genes. 24 cell types (avg. 1084±1156 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.637277648878577 accuracy

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(zebrafish_random), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(accuracy)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection ZEBRAFISH-RANDOM-F1: Label projection on Zebrafish (random split), F1 score

90k cells from zebrafish embryos throughout the first day of development, with and without a knockout of chordin, an important developmental gene. Split into train/test randomly. Dimensions: 26022 cells, 25258 genes. 24 cell types (avg. 1084±1156 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.5346413116985615 f1

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(zebrafish_random), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(f1)

Source checking is not independent reproduction.

scArches+scANVI (Seurat v3 2000 HVG) on Open Problems label projection ZEBRAFISH-RANDOM-F1-MACRO: Label projection on Zebrafish (random split), Macro F1 score

90k cells from zebrafish embryos throughout the first day of development, with and without a knockout of chordin, an important developmental gene. Split into train/test randomly. Dimensions: 26022 cells, 25258 genes. 24 cell types (avg. 1084±1156 cells per cell type).

Author-reported evaluation · Evaluation metadata: source checked

0.2832056442403825 f1-macro

Unit: fraction · Direction: higher

Uncertainty: Not reported

Scored: Not reported · Eligible: Not reported

source checkedopenproblems-label primary benchmark evidence · results, dataset(zebrafish_random), method(scarches_scanvi), paramset(Seurat v3 2000 HVG), metric(f1_macro)

Source checking is not independent reproduction.

Evidence table

Inspect claims, sources and review details

Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.

One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.

0 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-09-17-134cd1815de8
Property and statementOriginal source and locationReview and provenance

No evidence rows match these filters. Choose another scope or clear the search.

Sources and history

Release 2026-09-17-134cd1815de8 · Record review: source checked

1 source records and release historyDownload this release
Technical metadata and extraction receipts

Stable ID: open-problems-method-scarches-plus-scanvi-seurat-v3-2000-hvg

areas
cells-tissues
source locator
results, method(scarches_scanvi), paramset(Seurat v3 2000 HVG)
missing metadata
checkpoint revision: unreported; parameters: unextracted
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