Iterative point set registration for aligning scRNA-seq data.
Several studies profile similar single cell RNA-Seq (scRNA-Seq) data using different technologies and platforms. A number of alignment methods have been developed to enable the integration and comparison of scRNA-Seq data from such studies. While each performs well on some of the datasets, to date n...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2020-10-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1007939 |
| _version_ | 1818582270874746880 |
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| author | Amir Alavi Ziv Bar-Joseph |
| author_facet | Amir Alavi Ziv Bar-Joseph |
| author_sort | Amir Alavi |
| collection | DOAJ |
| description | Several studies profile similar single cell RNA-Seq (scRNA-Seq) data using different technologies and platforms. A number of alignment methods have been developed to enable the integration and comparison of scRNA-Seq data from such studies. While each performs well on some of the datasets, to date no method was able to both perform the alignment using the original expression space and generalize to new data. To enable such analysis we developed Single Cell Iterative Point set Registration (SCIPR) which extends methods that were successfully applied to align image data to scRNA-Seq. We discuss the required changes needed, the resulting optimization function, and algorithms for learning a transformation function for aligning data. We tested SCIPR on several scRNA-Seq datasets. As we show it successfully aligns data from several different cell types, improving upon prior methods proposed for this task. In addition, we show the parameters learned by SCIPR can be used to align data not used in the training and to identify key cell type-specific genes. |
| first_indexed | 2024-12-16T07:46:43Z |
| format | Article |
| id | doaj.art-df642de979004a4ca57cd54ef621881d |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-16T07:46:43Z |
| publishDate | 2020-10-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-df642de979004a4ca57cd54ef621881d2022-12-21T22:38:57ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582020-10-011610e100793910.1371/journal.pcbi.1007939Iterative point set registration for aligning scRNA-seq data.Amir AlaviZiv Bar-JosephSeveral studies profile similar single cell RNA-Seq (scRNA-Seq) data using different technologies and platforms. A number of alignment methods have been developed to enable the integration and comparison of scRNA-Seq data from such studies. While each performs well on some of the datasets, to date no method was able to both perform the alignment using the original expression space and generalize to new data. To enable such analysis we developed Single Cell Iterative Point set Registration (SCIPR) which extends methods that were successfully applied to align image data to scRNA-Seq. We discuss the required changes needed, the resulting optimization function, and algorithms for learning a transformation function for aligning data. We tested SCIPR on several scRNA-Seq datasets. As we show it successfully aligns data from several different cell types, improving upon prior methods proposed for this task. In addition, we show the parameters learned by SCIPR can be used to align data not used in the training and to identify key cell type-specific genes.https://doi.org/10.1371/journal.pcbi.1007939 |
| spellingShingle | Amir Alavi Ziv Bar-Joseph Iterative point set registration for aligning scRNA-seq data. PLoS Computational Biology |
| title | Iterative point set registration for aligning scRNA-seq data. |
| title_full | Iterative point set registration for aligning scRNA-seq data. |
| title_fullStr | Iterative point set registration for aligning scRNA-seq data. |
| title_full_unstemmed | Iterative point set registration for aligning scRNA-seq data. |
| title_short | Iterative point set registration for aligning scRNA-seq data. |
| title_sort | iterative point set registration for aligning scrna seq data |
| url | https://doi.org/10.1371/journal.pcbi.1007939 |
| work_keys_str_mv | AT amiralavi iterativepointsetregistrationforaligningscrnaseqdata AT zivbarjoseph iterativepointsetregistrationforaligningscrnaseqdata |