Website to share results of fucci-seq project.

Overview


Microscopy image analysis

We evaluated and pre-processed the results of image analysis as follows:

  1. We visually inspect images deteced to have none or more than one nucleus. For cases that are inconsistent with visual inspection, we correct the number of nuclei detected.
  2. We applied background correction to the intensity measurements of GFP, RFP and DAPI based on the following analyses.
  3. We analyzed intensity variation across individuals and batches and determined on an approach that removes batch effect in the data.

RNA-seq data preprcessing

  1. The first step in preprocessing RNA-seq data consists of QC and filtering.
  2. We then analyzed and corrected for batch effect due to C1 plate in the sequencing data

RNA-seq data cell cycle gene signal

We investigated cell cycle signals in the sequencing data.

  1. Investigate transgene count in sequencing data

  2. Select cell cycle genes for training data

  3. Correlation/association between expression and intensities

  4. [PCA and intensities


Intensity-based cell cycle labeling

We explored the possiblities of using intensities to learn cell cycle phases/genes in RNA-seq data.

  1. Consider categorical labeling
  2. Consider continuous ordering

Model fitting



One-time investigations


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