WGBS normalization methods inquiry

• MethylDackel

  1 153 3.0 C

  A (mostly) universal methylation extractor for BS-seq experiments.

Anyway, I'm curious if there are methods used to normalize the data to account for the difference in sequencing depth. I've already employed random subsampling like they used in the EpiQC study to achieve a similar mean coverage across the board, but I'm curious if there are any other known methods which minimize information loss. For context, I won't be doing DML/DMR detection (I know these methods can take coverage into account when merging DMRs and performing statistical analyses), but rather tissue of origin estimation between sets. My data are per-CpG context bedGraph files from MethylDackel, but I have access to the per-Cytosine bedGraphs all the way up to the raw FASTQ files.

• celfie

  1 27 3.8 Jupyter Notebook

  cfDNA cell type of origin estimation

I'm using CelFiE for tissue-of-origin estimation, for what it's worth.

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

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