1. Medicine
  2. Neuroscience

scAAVengr, a transcriptome-based pipeline for quantitative ranking of engineered AAVs with single-cell resolution

  1. Bilge E Öztürk
  2. Molly E Johnson
  3. Michael Kleyman
  4. Serhan Turunç
  5. Jing He
  6. Sara Jabalameli
  7. Zhouhuan Xi
  8. Meike Visel
  9. Valérie L Dufour
  10. Simone Iwabe
  11. Felipe Pompeo Marinho
  12. Gustavo D Aguirre
  13. José-Alain Sahel
  14. David V Schaffer
  15. Andreas R Pfenning
  16. John G Flannery
  17. William A Beltran
  18. William R Stauffer
  19. Leah C Byrne  Is a corresponding author
  1. University of Pittsburgh, United States
  2. Carnegie Mellon University, United States
  3. University of California, Berkeley, United States
  4. University of Pennsylvania, United States
https://doi.org/10.7554/eLife.64175
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  1. Bilge E Öztürk
  2. Molly E Johnson
  3. Michael Kleyman
  4. Serhan Turunç
  5. Jing He
  6. Sara Jabalameli
  7. Zhouhuan Xi
  8. Meike Visel
  9. Valérie L Dufour
  10. Simone Iwabe
  11. Felipe Pompeo Marinho
  12. Gustavo D Aguirre
  13. José-Alain Sahel
  14. David V Schaffer
  15. Andreas R Pfenning
  16. John G Flannery
  17. William A Beltran
  18. William R Stauffer
  19. Leah C Byrne
(2021)
scAAVengr, a transcriptome-based pipeline for quantitative ranking of engineered AAVs with single-cell resolution
eLife 10:e64175.
https://doi.org/10.7554/eLife.64175
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  1. Bilge E Öztürk
  2. Molly E Johnson
  3. Michael Kleyman
  4. Serhan Turunç
  5. Jing He
  6. Sara Jabalameli
  7. Zhouhuan Xi
  8. Meike Visel
  9. Valérie L Dufour
  10. Simone Iwabe
  11. Felipe Pompeo Marinho
  12. Gustavo D Aguirre
  13. José-Alain Sahel
  14. David V Schaffer
  15. Andreas R Pfenning
  16. John G Flannery
  17. William A Beltran
  18. William R Stauffer
  19. Leah C Byrne
(2021)
scAAVengr, a transcriptome-based pipeline for quantitative ranking of engineered AAVs with single-cell resolution
eLife 10:e64175.
https://doi.org/10.7554/eLife.64175