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Fig. 2 | BMC Bioinformatics

Fig. 2

From: Modeling and correct the GC bias of tumor and normal WGS data for SCNA based tumor subclonal population inferring

Fig. 2

The relationship of GC bias between paired tumor and normal samples. a The GC bias distribution of read count observed in 500bp bins with high mappability (top 10%). To account for uniqueness of sequences, a mappability measure is calculated for each position (base pair) in the bin. A location is called ‘mappable’ if the k-mer of the reference genome starting at the location is not perfectly repeated at any other location in the genome, where k is the read length. Both of the tumor and normal samples are processed by Illumina platform to produce the reads, and use GATK’s table recalibration and use Burrows-Wheeler Aligner (bwa) to align the sequence data with the same parameters. b In this figure, the red and blue solid lines are the mean functions of loess smooth in (a). The red and blue dashed lines are the mean functions of loess smooth in (a) multiplies exp(1.3GC)/(2.3GC) and exp(2GC)/(3GC) respectively

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