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High throughput re-sequencing uncovers various genetic variations by mapping the sequencing reads of related individuals to the reference genome.
FPKM values were obtained by mapping the sequencing reads (from all libraries) to the contigs with the program RNA-Seq by Expectation-Maximization (RSEM) v. 1.2.12 [ 55].
One way to avoid assembling and aligning sets of long sequences is to restrict the analysis to mapping the sequencing reads onto an existing reference genome.
After mapping the sequencing reads to the reference human genome (hg18), we determined methylation levels at target CpG sites as described previously [ 21].
After mapping the sequencing reads to the reference genome with TopHat, transcripts were assembled and their relative expression levels were calculated with Cufflinks in Fragments Per Kilobase of exon per Million fragments mapped (FPKM).
The mA modified regions can be identified by mapping the sequencing reads to the reference sequence of a genome through comparison of read counts between the sample and the control.
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Also, we compared the SCS and bareback-processed samples after mapping the sequences to the genome.
We did this by mapping the sequence of the probes, and determining their position in the gene with regard to the miRNA target sites predicted for the gene.
The probe sequence accuracy was validated by mapping the sequences to the Ae. tauschii Illumina reads representing 30X genome coverage.
By mapping the sequence reads back to pre-miRNAs, one can quantify the expression levels of mature miRNAs.
Further filtering was done by mapping the sequences containing SNPs to the E. guineensis genome scaffolds [ 1].
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