You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: manuscript.md
+38-12Lines changed: 38 additions & 12 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -9,7 +9,7 @@ keywords:
9
9
- open science
10
10
- reproducibility
11
11
lang: en-US
12
-
date-meta: '2026-01-12'
12
+
date-meta: '2026-01-13'
13
13
author-meta:
14
14
- Allegra G. Hawkins
15
15
- Joshua A. Shapiro
@@ -36,11 +36,11 @@ header-includes: |
36
36
<meta name="citation_title" content="The Single-cell Pediatric Cancer Atlas: Data portal and open-source tools for single-cell transcriptomics of pediatric tumors" />
37
37
<meta property="og:title" content="The Single-cell Pediatric Cancer Atlas: Data portal and open-source tools for single-cell transcriptomics of pediatric tumors" />
38
38
<meta property="twitter:title" content="The Single-cell Pediatric Cancer Atlas: Data portal and open-source tools for single-cell transcriptomics of pediatric tumors" />
from [AlexsLemonade/ScPCA-manuscript@0d5913b](https://github.com/AlexsLemonade/ScPCA-manuscript/tree/0d5913b9256ff4a452929c68030d05ab8f71b2ea)
124
-
on January 12, 2026.
123
+
from [AlexsLemonade/ScPCA-manuscript@7e4d905](https://github.com/AlexsLemonade/ScPCA-manuscript/tree/7e4d9053d8d1d2619806ef331d98138dededdac8)
124
+
on January 13, 2026.
125
125
</em></small>
126
126
127
127
@@ -541,6 +541,32 @@ However, there is notable heterogeneity even within HGG and LGG subtypes (Figure
541
541
Figure {@fig:fig4}D shows the expression of cell-type specific markers for all immune cell types, validating the assignment of various immune cell types with consensus cell types.
542
542
A summary of all the consensus cell types observed in all other ScPCA samples can be found in Figure {@fig:figS6}.
543
543
544
+
545
+
### Augmenting cell type annotations for malignant cell identification
546
+
547
+
Because the consensus annotations were derived from automated methods that do not specifically consider tumor cell states, they provide limited information for distinguishing malignant from normal cells.
548
+
We therefore sought complementary avenues to increase the value of cell type annotations with information that can be leveraged for this purpose.
549
+
550
+
In parallel to developing the ScPCA Portal, we launched the OpenScPCA project [@url: https://openscpca.readthedocs.io], an open-science collaborative initiative to further characterize and analyze Portal data.
551
+
Thus far, we have added manual cell type annotations for two projects, `SCPCP000004` (neuroblastoma) and `SCPCP000015` (Ewing sarcoma), to the Portal based on analyses performed in the OpenScPCA project.
552
+
Figure {@fig:fig5}A displays, for example, a UMAP of all libraries in `SCPCP000004` highlighting this project's OpenScPCA annotations which were derived using the `NBAtlas` dataset as reference [@doi:10.1016/j.celrep.2024.114804].
553
+
Unlike the consensus cell type annotations, the OpenScPCA project annotations distinguish between normal and malignant cells and contain far fewer uncharacterized cells.
554
+
Indeed, for `SCPCP000004`, the consensus cell type procedure labeled only ~43% of cells, but the OpenScPCA project labeled ~91% of cells, thereby adding substantial value to the data.
555
+
Note that the Portal's summary cell type report will include comparisons between annotations made in `scpca-nf` to OpenScPCA annotations for relevant libraries.
556
+
557
+
In an effort to identify potential malignant cells across all samples in the Portal, we included a step in the `scpca-nf` pipeline to run `InferCNV` [@url:https://github.com/broadinstitute/inferCNV] to quantify copy-number alterations (Figure {@fig:fig2}A).
558
+
The estimates complement the consensus cell types by providing a proxy for a cell's malignant status, such that cells with high levels of CNV are more likely to be tumor than normal cells.
559
+
Indeed, there is broad correspondence between malignant cells (Figure {@fig:fig5}A) and the total per-cell CNV across libraries in `SCPCP000004` (Figure {@fig:fig5}B); malignant cells tend to have higher levels of CNV, whereas normal cells tend to have lower levels of CNV.
560
+
We probed this relationship further within a single neuroblastoma library, `SCPCL000130`, finding clear signatures of canonical neuroblastoma CNV events such as `1q` loss, `11q` gain, and `17p` loss [@doi:10.1038/nrdp.2016.78; @doi:10.1016/j.celrep.2024.114804; @doi:10.1158/2159-8290.CD-14-0622] within malignant cells (Figure {@fig:fig5}C).
561
+
By contrast, normal cells show very few CNV events, consistent with their annotations.
562
+
Most intriguingly, unknown cells show CNV event signatures more similar to the malignant cells than to the normal cells, suggesting many of these cells may indeed be malignant.
563
+
564
+
We also see traces of this relationship even when looking at the consensus cell types in conjunction with CNV events.
565
+
In Figure {@fig:fig5}D, we show the distributions of per-cell total CNV events for the most commonly-observed consensus cell types in the neuroblastoma library `SCPCL000130`.
566
+
Here, Unknown and neuron cells have distinctly higher total CNV values compared to other cell types, suggesting that they are likely to be malignant cells.
567
+
We see similar patterns for the ganglioglioma library `SCPCL000049` (Figure {@fig:figS4}B-C), where consensus T cells have low total CNV values, while other cell types including oligodendrocyte precursor cells, neuron associated cells, and Unknown cells have much higher total CNV values.
568
+
As such, joint information from consensus cell type annotations and `InferCNV` results may be used to identify malignant cells across libraries in the Portal, including those which do not yet have associated OpenScPCA project annotations.
569
+
544
570
## Analysis of bulk RNA-seq
545
571
546
572
Several projects in the ScPCA Portal contain bulk RNA-seq data in addition to single-cell/nuclei RNA-seq data.
0 commit comments