@article {52, title = {A multi-task convolutional deep neural network for variant calling in single molecule sequencing.}, journal = {Nat Commun}, volume = {10}, year = {2019}, month = {2019 03 01}, pages = {998}, abstract = {

The accurate identification of DNA sequence variants is an important, but challenging task in genomics. It is particularly difficult for single molecule sequencing, which has a per-nucleotide error rate of ~5-15\%. Meeting this demand, we developed Clairvoyante, a multi-task five-layer convolutional neural network model for predicting variant type (SNP or indel), zygosity, alternative allele and indel length from aligned reads. For the well-characterized NA12878 human sample, Clairvoyante achieves 99.67, 95.78, 90.53\% F1-score on 1KP common variants, and 98.65, 92.57, 87.26\% F1-score for whole-genome analysis, using Illumina, PacBio, and Oxford Nanopore data, respectively. Training on a second human sample shows Clairvoyante is sample agnostic and finds variants in less than 2 h on a standard server. Furthermore, we present 3,135 variants that are missed using Illumina but supported independently by both PacBio and Oxford Nanopore reads. Clairvoyante is available open-source ( https://github.com/aquaskyline/Clairvoyante ), with modules to train, utilize and visualize the model.

}, keywords = {Base Sequence, Computational Biology, DNA Mutational Analysis, Genome, Human, Genome-Wide Association Study, Genomics, Genotype, Genotyping Techniques, Humans, INDEL Mutation, Nanopores, Neural Networks (Computer), Polymorphism, Single Nucleotide, Sequence Analysis, DNA, Software}, issn = {2041-1723}, doi = {10.1038/s41467-019-09025-z}, author = {Luo, Ruibang and Sedlazeck, Fritz J and Lam, Tak-Wah and Schatz, Michael C} } @article {37, title = {Accurate detection of complex structural variations using single-molecule sequencing.}, journal = {Nat Methods}, volume = {15}, year = {2018}, month = {2018 06}, pages = {461-468}, abstract = {

Structural variations are the greatest source of genetic variation, but they remain poorly understood because of technological limitations. Single-molecule long-read sequencing has the potential to dramatically advance the field, although high error rates are a challenge with existing methods. Addressing this need, we introduce open-source methods for long-read alignment (NGMLR; https://github.com/philres/ngmlr ) and structural variant identification (Sniffles; https://github.com/fritzsedlazeck/Sniffles ) that provide unprecedented sensitivity and precision for variant detection, even in repeat-rich regions and for complex nested events that can have substantial effects on human health. In several long-read datasets, including healthy and cancerous human genomes, we discovered thousands of novel variants and categorized systematic errors in short-read approaches. NGMLR and Sniffles can automatically filter false events and operate on low-coverage data, thereby reducing the high costs that have hindered the application of long reads in clinical and research settings.

}, keywords = {DNA Mutational Analysis, Genome, Human, Genomics, High-Throughput Nucleotide Sequencing, Humans, Sequence Analysis, DNA}, issn = {1548-7105}, doi = {10.1038/s41592-018-0001-7}, author = {Sedlazeck, Fritz J and Rescheneder, Philipp and Smolka, Moritz and Fang, Han and Nattestad, Maria and von Haeseler, Arndt and Schatz, Michael C} } @article {40, title = {Complex rearrangements and oncogene amplifications revealed by long-read DNA and RNA sequencing of a breast cancer cell line.}, journal = {Genome Res}, volume = {28}, year = {2018}, month = {2018 08}, pages = {1126-1135}, abstract = {

The SK-BR-3 cell line is one of the most important models for HER2+ breast cancers, which affect one in five breast cancer patients. SK-BR-3 is known to be highly rearranged, although much of the variation is in complex and repetitive regions that may be underreported. Addressing this, we sequenced SK-BR-3 using long-read single molecule sequencing from Pacific Biosciences and develop one of the most detailed maps of structural variations (SVs) in a cancer genome available, with nearly 20,000 variants present, most of which were missed by short-read sequencing. Surrounding the important oncogene (also known as ), we discover a complex sequence of nested duplications and translocations, suggesting a punctuated progression. Full-length transcriptome sequencing further revealed several novel gene fusions within the nested genomic variants. Combining long-read genome and transcriptome sequencing enables an in-depth analysis of how SVs disrupt the genome and sheds new light on the complex mechanisms involved in cancer genome evolution.

}, keywords = {Breast Neoplasms, Female, Gene Amplification, Gene Rearrangement, Genome, Human, Genomic Structural Variation, High-Throughput Nucleotide Sequencing, Humans, MCF-7 Cells, Oncogenes, Receptor, ErbB-2, Repetitive Sequences, Nucleic Acid, Transcriptome}, issn = {1549-5469}, doi = {10.1101/gr.231100.117}, author = {Nattestad, Maria and Goodwin, Sara and Ng, Karen and Baslan, Timour and Sedlazeck, Fritz J and Rescheneder, Philipp and Garvin, Tyler and Fang, Han and Gurtowski, James and Hutton, Elizabeth and Tseng, Elizabeth and Chin, Chen-Shan and Beck, Timothy and Sundaravadanam, Yogi and Kramer, Melissa and Antoniou, Eric and McPherson, John D and Hicks, James and McCombie, W Richard and Schatz, Michael C} }