  Bursting cells lead to ambient RNA that contaminates sequencing data. This
process is especially problematic in perturbation experiments where
transcription factors are implanted into cells to determine their effects. The
presence of contaminants makes it difficult to determine whether a factor is
truly expressed in the cell. This paper studies the properties of contaminant
noise from an analytical perspective, showing that the cell bursting process
constrains the form of the noise distribution across factors. These constraints
can be leveraged to improve decontamination by removing counts that are more
likely the result of noise than expression. In two biological replicates of a
perturbation experiment, run across two sequencing protocols, decontaminated
counts agree with bulk genomic measurements of the transduction rate and are
automatically corrected for differences in sequencing.
