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Genotype imputation allows different marker panels to be combined and missing genotypes to be infered in silico.
A less expensive approach to produce sequence genotypes for a large number of individuals is to impute from lower density marker panels to whole-genome sequence data.
This is consistent with the previous inclusion of MAL2 in marker panels to discriminate pancreatic cancer from pancreatitis [ 26] and metastatic from non-affected lymph nodes in colorectal cancer patients [ 27].
Further, considering that no single methylated gene was detected in any breast cancer types, it is necessary to use cancer-specific methylation marker panels to screen breast cancer [24].
This study focuses on alternative low-cost genomic selection methods (IBD-GS) that use selective genotyping with sparse marker panels to estimate identity-by-descent relationships through linkage analysis.
However, given the sensitive and high-throughput quantitative methodologies for methylation analysis, specific markers for HNC will certainly emerge by careful evaluation and combination of different marker panels to achieve a high sensitivity for the disease.
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We therefore tested, if the observed fluctuations in marker levels and status alter the capability of the glycan marker panel to differentiate between CD versus UC and their association with CD phenotypes.
In summary, we established an appropriate marker panel to distinguish marmoset TMSCs and spermatogonia.
ROC analysis was first conducted on individual markers and then on their combination to explore the possibility of a marker panel to lead to improved performance.
Based on these simulated marker genotype data sets, we apply our algorithm on the marker panel to obtain the most diverse reference panels of 200 haplotypes.
ELF3, EphB4, EpCAM, EGFR, CEA and MGB1 are appropriate RT-PCR markers for use in a marker panel to detect disseminated breast cancer cells after immunomagnetic enrichment.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com