LoFreq: a sequence-quality aware, ultra-sensitive variant caller for uncovering cell-population heterogeneity from high-throughput sequencing datasets

By Andreas Wilm, P. Aw, D. Bertrand, G. Yeo, S. Ong, C. Wong, C. Khor, R. Petric, M. Hibberd, Niranjan Nagarajan. Nucleic Acids Research, 2012

1,315 citations recorded by the source corpus.

The study of cell-population heterogeneity in a range of biological systems, from viruses to bacterial isolates to tumor samples, has been transformed by recent advances in sequencing throughput. While the high-coverage afforded can be used, in principle, to identify very rare variants in a population, existing ad hoc approaches frequently fail to distinguish true variants from sequencing errors. We report a method (LoFreq) that models sequencing run-specific error rates to accurately call variants occurring in <0.05% of a population. Using simulated and real datasets (viral, bacterial and human), we show that LoFreq has near-perfect specificity, with significantly improved sensitivity compared with existing methods and can efficiently analyze deep Illumina sequencing datasets without resorting to approximations or heuristics. We also present experimental validation for LoFreq on two different platforms (Fluidigm and Sequenom) and its application to call rare somatic variants from exome sequencing datasets for gastric cancer. Source code and executables for LoFreq are freely available at http://sourceforge.net/projects/lofreq/.

Subfields: Cancer Research, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/0b156c980dbd38ec3fd54799d317c7385e582fc0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cancer Research

1. Aviv Regev
2. Niko Beerenwinkel
3. Moritz Gerstung
4. Lieven Clement
5. John G. Tate

In Genetics

1. Aviv Regev
2. Mile Sikic
3. Florian Markowetz
4. Roland F. Schwarz
5. Niranjan Nagarajan
6. Niko Beerenwinkel
7. Moritz Gerstung
8. Bradley E. Bernstein

In Molecular Biology

1. Aviv Regev
2. Florian Markowetz
3. Fiona Cunningham
4. Anja Thormann
5. Mile Sikic
6. Benjamin L. Moore
7. Niranjan Nagarajan
8. Niko Beerenwinkel

Citations in the corpus

• Fast and sensitive mapping of nanopore sequencing reads with GraphMap (2016, methodology): “For each seed hit to a bin, it increments the value of the bin corresponding to its c parameter value determined using equation (3).”
• Ensembl 2021 (2020, methodology): “pipeline employing LoFreq (44) to identify variants in publicly available SARS-CoV-2 genomes sequenced and deposited in the European Nucleotide Archive.”
• Cancer Evolution: Mathematical Models and Computational Inference (2014, methodology): “…either employ frequentist statistical methods for modeling the distribution of variants per site in the genome, such as deepSNV (Gerstung et al. 2012), Varscan (Koboldt et al. 2012), and LoFreq (Wilm et al. 2012), or employ a Bayesian classifier framework, such as MuTect (Cibulskis et al. 2013).”
• ViVaMBC: estimating viral sequence variation in complex populations from illumina deep-sequencing data using model-based clustering (2015, methodology): “[10], among others, have shown that incorporating quality scores improves sensitivity without loss of specificity.”
• Single-cell transcriptomic analysis of primary and metastatic tumor ecosystems in head and neck cancer (2017, methodology): “Single nucleotide and indel variants were detected using MuTect1 (Cibulskis et al., 2013), LoFreq (Wilm et al., 2012), and GATK (DePristo et al., 2011; McKenna et al., 2010; Van der Auwera et al., 2013).”