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A number of algorithms rely on some form of cross-correlation between positive- and negative-strand read sets to estimate fragment length (details provided later in the text).
Given enough diversity in overlap regions, the concordance of variant frequencies can be used to estimate fragment specific template input and accuracy of SNP frequencies.
When those computations are carried out to estimate fragment length, and when the bias is strong enough, a dramatically wrong fragment-length estimate can result.
The essence of our proposal is to use cross-correlation to estimate fragment length, but to compute it using only bases where the positive strand and the shifted negative strand are both mappable (Fig. 3).
On a single core of a SunFire x2250 computer with 32 Gb RAM, it takes on average ∼30 min to estimate fragment length for each of the datasets studied in this article.
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Cufflinks (v. 2.0.2) were used to estimate fragments per kilobase of exon per million fragments mapped (FPKM) values for University of California Santa Cruz Genome Database known genes.
Alternatively, for approaches (2 - 6), we implemented the program Cufflinks v1.0.3 [ 34] to estimate fragments per kilobase of exon per million fragments (FPKM) – an index typically used in RNA-seq analyses – using different annotations with the same mapping results files.
To detected fluorescent signals with Genescan 3.1 software, and we estimated fragment sizes with Genescan 3.1 software referring to GeneScan™ -500ROX™ standard.
Capillary electrophoresis consistently estimated fragment sizes larger than direct sequencing of the different alleles, regardless of the dye (FAM or VIC) used for labeling.
Complexity of the sequencing libraries was estimated, fragments mapped to the genome, and peaks called as described in Wei et al. (2008).
Results: In this article, we investigate the use of strand cross-correlation to estimate mean fragment length of single-end data and show that traditional estimation approaches have mixed reliability.
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