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To obtain copy numbers, we calculated reads per million per kilobase for all open reading frames.

To summarize the gene model read density patterns genome-wide, we calculated read coverage at multiple gene model features.

In this study, those sequencing reads were mapped onto the complete MED mitogenome and the numbers of reads per base calculated (read coverage).

First, we aligned all the reads and calculated reads per kilobase per million (RPKM) for each exon using Bioscope 1.3 software package [ 30].

To quantify the effectiveness of "filter enabled frequency-weighted method", the extent of abundance profile correction was calculated by averaging the absolute differences of calculated read count vs real read count of all the KO-families.

We used BWA 0.6.3 to map reads, calculated reads per kilobase transcript per million (RPKM), and normalized the data using a standard quantile normalization approach (for example, as in [ 26]).

For RNA-Seq datasets, we collected only reads that locate on exons as annotated in NCBI Reference Sequence Database (RefSeq) for assembly mm9, and calculated reads per kilobase per million (RPKM) for each gene as measure of expression level.

To quantify expression levels and the strength of KAP1 and SETDB1 marks, we calculated reads per kilobase per million mapped reads (RPKM) [ 77, 78] for genomic regions of interest.

seqMINER [ 20] was used to calculate read counts and produce heatmaps of read enrichment at TSS.

The mapped reads were then used to calculate read counts for annotated genes.

USeq was also used to calculate reads per kilobase exon per million reads (RPKM) and fold change values between conditions.

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