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Concordance between HLA alleles genotyped using sanger sequencing and Illumina short-reads via Heng Li bwa-alt pipeline
Genotyping HLA alleles in samples that have been sequenced using Illumina short-reads is a challenging (Brandt et al (2015)) and non-trivial task. Different approaches have been developed in recent years (Warren et al (2012), Liu et al (2013), Bai et al (2014), Dilthey et al (2015), Xie et al (2017)).
Based on PCA, an overview of the genotype concordance between Illumina ultra high-coverage (~200x), Illumina high-coverage (~30x), Illumina low-coverage (~7x), Complete Genomics high-coverage (versions 2.0 and 2.2, from ~30x to ~87x) and BGIseq-500 high-coverage (PE100, ~37x) platforms/sequencing-runs. For this purpose I used 12 reference samples for which there are available data in at least two or more of the previous technologies.
In the supplementary section 1 of the Simons Genome Diversity Project, Mallik et al. introduce the use of non-standard (not part of the best practises and default setting of GATK) snp calling priors. The default snp calling priors in GATK they write, “have built-in priors for Bayesian SNP calling that assume that the site is more likely to be homozygous for the reference allele than homozygous for the variant allele. When there is ambiguity in a heterozygous, GATK prefers the reference homozygous. This is a reference bias, and while this bias is not typically problematic for medical studies*, it can complicate interpretation of population genetics signals … “
[Report] Using transcriptomes to search for positive selection and adaptation in gene expression of Drosophila species
To be finished, …
To be written, …
While SNP ascertainment bias is a well known issue in SNP array-based studies (Clark et al (2005), Albrechtsen et al (2010), Lachance et al (2013)), I have not been able to find a published study or discussion in the Internet about the impact that SNP selection bias can have on amixture analysis using the software admixture (Alexander et al (2009)).
A flexible tool that specifically addresses the shortcomings of ancient dna to identify Y haplogroups in an automated and reliable
The plan is to use Eurasian high-coverage genomes in order to detect the footprint of the 13th-14th centuries Black death in Europe
Building a high-confidence call set for Y chromosome SNVs and structural variants based o short and ĺong reads using reference samples