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To assist the mapping rates for the unmapped data, the ArcGIS address locator was used.
The clean reads, mapped reads, uniquely mapped reads and mapping rates for all 22 samples are listed in Supplementary information, Table S1.
In the "transcriptome + genome" mapping mode, the average mapping rates for Ensembl, RefGene, and UCSC increased to 96.7%, 94.5%, and 94.6%, respectively, and the mapping rate difference among different gene models decreased.
In all, 52 and 59 million 1 × 100 single reads of the paired CRC/control mucosa RNA samples were obtained and were uniquely mapped to the hg19 genome with over 85% of mapping rates for both cases.
As before, sequencing errors increased the fraction of SNPs that had unequal mapping rates for the two alleles, but there was not a substantial average bias toward the reference allele.
The mapping rates for reads from brother (II-1) and sister (II-2) were 98.4% and 98.8%, respectively, and the on-target rates (fraction of reads mapped to designed exome regions) were 54.9% and 58.4%, respectively.
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The corresponding mapping rate for genomic or transcriptomic alignments was 96%.
peruviana mapped reads showed an overall 92.51 % mapping rate for PAB-4377 and 95.87 % for LEM1537 against L. (V).
However, we observed a general higher mapping rate for every P-VDJ tagged pool compared to P-U pool from the same dataset.
Using Gencode gtf as the reference, the mapping rate for each sample is between 93.2 % and 94.6 % (Additional file 1: Table S2).
Second, with respect to small RNAs, the list of candidates was very short, and the overall mapping rate for small RNAs was much lower than for longer transcripts (Tables 1 and 2).
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