Sentence examples for downstream estimation from inspiring English sources

As NAF in combination with the MS-based analysis is a complex procedure, various error sources can affect the compartmental separation and downstream estimation of subcellular distributions.

Although discarding reads with multiple mappings is a common practice (1, 5, 10, 11), their exclusion can lead to additional biases in downstream estimation (4).

Simulation of downstream speed estimation using populations of speed-tuned units showed that peak (winner take all) readout provided more precise speed estimates than centroid (vector average) readout.

As in our study silver bioavailability was only considered for the WWTP effluent, but not with regard to the environmental fate further downstream, our estimation of the aquatic toxicity potential is probably overestimated.

(XLSX 63 kb) Additional file 8: Phylogeny reconstructed from non-tip SNPs in non-recombinant genomic regions for downstream ancestral character estimation.

This suggests that the asymmetry in HGDP Yoruba REHH, between 5′ and 3′ regions, may reflect technical artefacts affecting haplotype estimation downstream (e.g. assay performance, phasing accuracy) rather than a biological signal (e.g. selection acting on sequences upstream of T1264G).

In the second part of the study, the models were compared to each other in estimation of downstream suspended sediment data by using data from both stations.

A straightforward way to assemble transcriptomes for multiple samples is to "merge" all transcripts that are assembled from individual samples as a "universal" set of isoforms, which is then used for downstream applications including abundance estimation and differential analysis.

Despite the fact that accurate SNP and genotype calling is fundamental for precise population parameter estimation in downstream analyses [ 17, 40, 41], to our knowledge direct comparisons of different SNP callers in the aforementioned context are still scarce.

The primary reason for this is that census forecasts beyond 1-day rely heavily on accurate predictions of the number of arrivals for intermediary days, thus bias in intermediary predictions can give rise to considerable under- over-estimation in downstream census forecasts.

The consequent multiple alignments and misalignments lead to problems in downstream analysis, including the abundance estimation and the structural variation (SV) calling.