Identification and Correction of Time-Series Transcriptomic Anomalies[K562_timeseries]

Analysis and visualization of time-series transcriptomic data revealed Sudden TRanscriptomic Irregular Profile Expression changes (STRIPEs), characterized by anomalous transcript level values across the transcriptome in a given time point. We developed quantitative methods for detection and correction of STRIPEs in time-series. Correction of STRIPEs improves the quality of downstream analyses and reproducibility.Here we present cell-cycle transcriptomic time-series experiments containing STRIPEs from two different organisms/experimental conditions: Saccharomyces cerevisiae (BF264-15D background) in YEP 2% Dextrose at 38.5°C (mild chronic heat stress) and the K562 human cell line in RPMI + 10% BCS (bovine calf serum) + P/S. Overall design: For each time-series cell-cycle experiment, cells were first cell-cycle synchronized using alpha factor mating pheromone or centrifugal elutriation for the S. cerevisiae 38.5°C and the human k562 cell line datasets respectively. Cells were then grown in their respective environmental conditions [Saccharomyces cerevisiae (BF264-15D background) in YEP 2% Dextrose at 38.5°C (mild chronic heat stress) and the K562 human cell line in RPMI + 10% BCS (bovine calf serum) + P/S.] and samples were collected in time-series for RNA sequencing.