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High-content image analysis/dimensionality reduction of drug screening data (A–C) Representative data of high content analysis across six GSC lines and three compound libraries (LOPAC, (A) <t>Prestwick</t> <t>FDA</t> (B) and C3L, (C) by 3D principal component analysis (PCA) (median aggregation to well level, n = 6 fields of view). DMSO controls circled in Black ( n = 48 per plate). Magnitude of vector co-ordinates for PC1, 2, 3 (sized by PC4) are indicated by color, red-pink (strong –PC1, –PC2), blue (strong +PC3, –PC2), green (strong +PC1 +PC2), yellow/gray (weaker phenotypes). PC1-4 factor loadings are given (%). Factor loadings are provided in . (D–F) Phenotypic distance of screened compounds (LOPAC, D, Prestwick FDA, E and C3L, F). We employed 20 principal components (>60% explained variance) to compute a phenotypic distance (Euclidean) for each compound. The corresponding p values are plotted against cell survival (normalized z scores, y axis). Legend indicates strength of –log 10 [ p value] distribution (five bins, red = maximal effect, reducing to gray where at = arbitrary threshold). Several example hits are labeled.
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High-content image analysis/dimensionality reduction of drug screening data (A–C) Representative data of high content analysis across six GSC lines and three compound libraries (LOPAC, (A) <t>Prestwick</t> <t>FDA</t> (B) and C3L, (C) by 3D principal component analysis (PCA) (median aggregation to well level, n = 6 fields of view). DMSO controls circled in Black ( n = 48 per plate). Magnitude of vector co-ordinates for PC1, 2, 3 (sized by PC4) are indicated by color, red-pink (strong –PC1, –PC2), blue (strong +PC3, –PC2), green (strong +PC1 +PC2), yellow/gray (weaker phenotypes). PC1-4 factor loadings are given (%). Factor loadings are provided in . (D–F) Phenotypic distance of screened compounds (LOPAC, D, Prestwick FDA, E and C3L, F). We employed 20 principal components (>60% explained variance) to compute a phenotypic distance (Euclidean) for each compound. The corresponding p values are plotted against cell survival (normalized z scores, y axis). Legend indicates strength of –log 10 [ p value] distribution (five bins, red = maximal effect, reducing to gray where at = arbitrary threshold). Several example hits are labeled.
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High-content image analysis/dimensionality reduction of drug screening data (A–C) Representative data of high content analysis across six GSC lines and three compound libraries (LOPAC, (A) <t>Prestwick</t> <t>FDA</t> (B) and C3L, (C) by 3D principal component analysis (PCA) (median aggregation to well level, n = 6 fields of view). DMSO controls circled in Black ( n = 48 per plate). Magnitude of vector co-ordinates for PC1, 2, 3 (sized by PC4) are indicated by color, red-pink (strong –PC1, –PC2), blue (strong +PC3, –PC2), green (strong +PC1 +PC2), yellow/gray (weaker phenotypes). PC1-4 factor loadings are given (%). Factor loadings are provided in . (D–F) Phenotypic distance of screened compounds (LOPAC, D, Prestwick FDA, E and C3L, F). We employed 20 principal components (>60% explained variance) to compute a phenotypic distance (Euclidean) for each compound. The corresponding p values are plotted against cell survival (normalized z scores, y axis). Legend indicates strength of –log 10 [ p value] distribution (five bins, red = maximal effect, reducing to gray where at = arbitrary threshold). Several example hits are labeled.
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High-content image analysis/dimensionality reduction of drug screening data (A–C) Representative data of high content analysis across six GSC lines and three compound libraries (LOPAC, (A) <t>Prestwick</t> <t>FDA</t> (B) and C3L, (C) by 3D principal component analysis (PCA) (median aggregation to well level, n = 6 fields of view). DMSO controls circled in Black ( n = 48 per plate). Magnitude of vector co-ordinates for PC1, 2, 3 (sized by PC4) are indicated by color, red-pink (strong –PC1, –PC2), blue (strong +PC3, –PC2), green (strong +PC1 +PC2), yellow/gray (weaker phenotypes). PC1-4 factor loadings are given (%). Factor loadings are provided in . (D–F) Phenotypic distance of screened compounds (LOPAC, D, Prestwick FDA, E and C3L, F). We employed 20 principal components (>60% explained variance) to compute a phenotypic distance (Euclidean) for each compound. The corresponding p values are plotted against cell survival (normalized z scores, y axis). Legend indicates strength of –log 10 [ p value] distribution (five bins, red = maximal effect, reducing to gray where at = arbitrary threshold). Several example hits are labeled.
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High-content image analysis/dimensionality reduction of drug screening data (A–C) Representative data of high content analysis across six GSC lines and three compound libraries (LOPAC, (A) <t>Prestwick</t> <t>FDA</t> (B) and C3L, (C) by 3D principal component analysis (PCA) (median aggregation to well level, n = 6 fields of view). DMSO controls circled in Black ( n = 48 per plate). Magnitude of vector co-ordinates for PC1, 2, 3 (sized by PC4) are indicated by color, red-pink (strong –PC1, –PC2), blue (strong +PC3, –PC2), green (strong +PC1 +PC2), yellow/gray (weaker phenotypes). PC1-4 factor loadings are given (%). Factor loadings are provided in . (D–F) Phenotypic distance of screened compounds (LOPAC, D, Prestwick FDA, E and C3L, F). We employed 20 principal components (>60% explained variance) to compute a phenotypic distance (Euclidean) for each compound. The corresponding p values are plotted against cell survival (normalized z scores, y axis). Legend indicates strength of –log 10 [ p value] distribution (five bins, red = maximal effect, reducing to gray where at = arbitrary threshold). Several example hits are labeled.
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High-content image analysis/dimensionality reduction of drug screening data (A–C) Representative data of high content analysis across six GSC lines and three compound libraries (LOPAC, (A) <t>Prestwick</t> <t>FDA</t> (B) and C3L, (C) by 3D principal component analysis (PCA) (median aggregation to well level, n = 6 fields of view). DMSO controls circled in Black ( n = 48 per plate). Magnitude of vector co-ordinates for PC1, 2, 3 (sized by PC4) are indicated by color, red-pink (strong –PC1, –PC2), blue (strong +PC3, –PC2), green (strong +PC1 +PC2), yellow/gray (weaker phenotypes). PC1-4 factor loadings are given (%). Factor loadings are provided in . (D–F) Phenotypic distance of screened compounds (LOPAC, D, Prestwick FDA, E and C3L, F). We employed 20 principal components (>60% explained variance) to compute a phenotypic distance (Euclidean) for each compound. The corresponding p values are plotted against cell survival (normalized z scores, y axis). Legend indicates strength of –log 10 [ p value] distribution (five bins, red = maximal effect, reducing to gray where at = arbitrary threshold). Several example hits are labeled.
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Image Search Results


High-content image analysis/dimensionality reduction of drug screening data (A–C) Representative data of high content analysis across six GSC lines and three compound libraries (LOPAC, (A) Prestwick FDA (B) and C3L, (C) by 3D principal component analysis (PCA) (median aggregation to well level, n = 6 fields of view). DMSO controls circled in Black ( n = 48 per plate). Magnitude of vector co-ordinates for PC1, 2, 3 (sized by PC4) are indicated by color, red-pink (strong –PC1, –PC2), blue (strong +PC3, –PC2), green (strong +PC1 +PC2), yellow/gray (weaker phenotypes). PC1-4 factor loadings are given (%). Factor loadings are provided in . (D–F) Phenotypic distance of screened compounds (LOPAC, D, Prestwick FDA, E and C3L, F). We employed 20 principal components (>60% explained variance) to compute a phenotypic distance (Euclidean) for each compound. The corresponding p values are plotted against cell survival (normalized z scores, y axis). Legend indicates strength of –log 10 [ p value] distribution (five bins, red = maximal effect, reducing to gray where at = arbitrary threshold). Several example hits are labeled.

Journal: iScience

Article Title: A comprehensive pharmacological survey across heterogeneous patient-derived glioblastoma stem cell models

doi: 10.1016/j.isci.2026.115839

Figure Lengend Snippet: High-content image analysis/dimensionality reduction of drug screening data (A–C) Representative data of high content analysis across six GSC lines and three compound libraries (LOPAC, (A) Prestwick FDA (B) and C3L, (C) by 3D principal component analysis (PCA) (median aggregation to well level, n = 6 fields of view). DMSO controls circled in Black ( n = 48 per plate). Magnitude of vector co-ordinates for PC1, 2, 3 (sized by PC4) are indicated by color, red-pink (strong –PC1, –PC2), blue (strong +PC3, –PC2), green (strong +PC1 +PC2), yellow/gray (weaker phenotypes). PC1-4 factor loadings are given (%). Factor loadings are provided in . (D–F) Phenotypic distance of screened compounds (LOPAC, D, Prestwick FDA, E and C3L, F). We employed 20 principal components (>60% explained variance) to compute a phenotypic distance (Euclidean) for each compound. The corresponding p values are plotted against cell survival (normalized z scores, y axis). Legend indicates strength of –log 10 [ p value] distribution (five bins, red = maximal effect, reducing to gray where at = arbitrary threshold). Several example hits are labeled.

Article Snippet: Prestwick FDA approved Drug Library , Prestwick Chemical , https://www.prestwickchemical.com/screening-libraries/prestwick-chemical-library/.

Techniques: Drug discovery, High Content Screening, Plasmid Preparation, Labeling