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Genomics Articles

Recent genomic discoveries and advances

Genomics articles highlighting breakthroughs and advances in bioinformatics and clinical research from Illumina scientists and thought leaders

Discoveries by Illumina Scientists

Identifying Genomic Regions with High Quality Single Nucleotide Variant Calling

We can use aggregated alignment metrics from populations to predict how well we can call variants in any sample. This empirical approach finds very high quality regions and outperforms reference-based methods.

数据解决方案助力群体基因组学研究

Illumina Connected Analytics (ICA)平台是构建定制基因组分析环境的基础,负责管理并处理大量异质性数据集。

使用DRAGEN Bio-IT平台从PopGen数据集中准确高效地检出大小变异

DRAGEN平台以高精度和速度从群体遗传学研究中检出大小变异。

DRAGEN在PrecisionFDA Truth Challenge V2挑战赛中通过Alt-aware定位和Graph参考基因组展示了较高的准确性

DRAGEN最近赢得了PrecisionFDA Truth Challenge V2挑战赛,挑战赛针对难绘制和所有基准区域类别的Illumina read。

Spinal Muscular Atrophy Diagnosis and Carrier Screening from Whole Genome Sequencing Data

SMNCopyNumberCaller enables accurate copy number calling of the highly similar SMN1 and SMN2 for spinal muscular atrophy diagnosis/carrier screening.

REViewer: A Method for Visualizing Alignments of Short Reads in Regions Containing Long Repeat Expansions

REViewer is a computational method for visualization of sequencing data in genomic regions containing long repeat expansions.

Predicting Splicing from Primary Sequence with Deep Learning

SpliceAI, a 32-layer deep neural network, predicts splicing from pre-mRNA sequences and identifies cryptic splice variants in rare disease patients.

Predicting the Clinical Impact of Human Mutation with Deep Neural Networks

The Illumina team developed deep neural network algorithm, PrimateAI, to predict the clinical impact of human missense mutations.

Cyrius: Accurate CYP2D6 Genotyping Using Whole Genome Sequencing Data

CYP2D6 metabolizes 21% of clinically used drugs. Cyrius resolves common SVs and sequence homology to paralog and genotypes CYP2D6 with 99.3% accuracy.

Accurate Genotyping of Structural Variant Using Graph Model and Population Information

Paragraph is a graph aligner and variant caller that can accurately genotype known structural variants using the aligned sequence reads.