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LIU LAB @ USF

Bioinformatics

  • ​dbNSFP: dbNSFP is a database developed for functional prediction and annotation of all potential non-synonymous single-nucleotide variants (nsSNVs) in the human genome. ​
  • Access points
  1. ​Liu lab webservice: providing update information, download links and webservice. 
  2. google sites: providing update information and download links. 
  • Cite our papers
  1. Liu X, Jian X, and Boerwinkle E. 2011. dbNSFP: a lightweight database of human non-synonymous SNPs and their functional predictions. Human Mutation. 32:894-899.
  2. Liu X, Jian X, and Boerwinkle E. 2013. dbNSFP v2.0: A Database of Human Non-synonymous SNVs and Their Functional Predictions and Annotations. Human Mutation. 34:E2393-E2402. 
  3. Liu X, Wu C, Li C, and Boerwinkle E. 2016. dbNSFP v3.0: A One-Stop Database of Functional Predictions and Annotations for Human Non-synonymous and Splice Site SNVs. Human Mutation. 37(3):235-241. 
  4. Liu X, Li C, Mou C, Dong Y, and Tu Y. 2020. dbNSFP v4: a comprehensive database of transcript-specific functional predictions and annotations for human nonsynonymous and splice-site SNVs. Genome Medicine. 12:103. 
If you used dbNSFP v1.x, please cite our paper 1. If you used dbNSFP v2.x, please cite our papers 1 & 2. If you used dbNSFP v3.x, please cite our papers 1 & 3. If you used dbNSFP v4.x, please cite our papers 1 & 4.
  • dbscSNV: dbscSNV includes all potential human SNVs within splicing consensus regions (−3 to +8 at the 5’ splice site and −12 to +2 at the 3’ splice site), i.e. scSNVs, related functional annotations and two ensemble prediction scores for predicting their potential of altering splicing. dbscSNV can be queried as an attached database for dbNSFP.
  • Access point
  1. ​google sites (attached database of dbNSFP): providing update information and download links. 
  • Cite our paper
  1. Jian X, Boerwinkle E and Liu X. 2015. In silico prediction of splice-altering single nucleotide variants in the human genome. Nucleic Acids Research 42(22):13534-13544.
  • WGSA: WGSA is an annotation pipeline for human genome re-sequencing studies, to facilitate the functional annotation step of whole genome sequencing (WGS). Currently WGSA supports the annotation of SNVs and indels locally without remote database requests, allowing it to scale up for large WGS studies.
  • Access point
  1. ​google sites: providing update information and download links. 
  • Cite our paper
  1. Liu X, White S, Peng B, Johnson AD, Brody JA, Li AH, Huang Z, Carroll A, Wei P, Gibbs R, Klein RJ and Boerwinkle E. 2016. WGSA: an annotation pipeline for human genome sequencing studies. Journal of Medical Genetics 53:111-112. 
  • dbMTS: the database for miRNA target site (MTS) SNVs, which includes all potential MTS SNVs in the 3’UTR of human genome along with hundreds of functional annotations. This database can help studies easily identify putative SNVs that affect miRNA targeting and facilitate the prioritization of their functional importance.  dbMTS can be queried as an attached database for dbNSFP.
  • Access points
  1. ​Liu lab webservice: providing update information, download links and webservice. 
  2. google sites (attached database of dbNSFP): providing update information and download links. 
  • Cite our paper
  1. Li C, Mou C, Swartz MD, Yu B, Bai Y, Tu Y, Liu X. (2020) dbMTS: a comprehensive database of putative human microRNA target site SNVs and their functional predictions. Human Mutation 41(6):1123–1130. [preprint]
  • MetaRNN: a deep learning based ensemble pathogenicity prediction score for nsSNVs and non-frameshift indels. MetaRNN used a recurrent neural network (RNN) to integrate information from 16 high-level pathogenicity prediction scores, 8 conservation scores, and allele frequency information from the 1000 Genomes Project (1000GP), ExAC, and gnomAD.
  • Access points
  1. ​Liu lab webservice: providing update information, download links and webservice. 
  • ​Cite our paper
  1. Li C, Zhi D, Wang K, Liu X (2021) MetaRNN: Differentiating Rare Pathogenic and Rare Benign Missense SNVs and InDels Using Deep Learning. bioRxiv. https://doi.org/10.1101/2021.04.09.438706. [PDF]

Population Genetics

  • ​SRV: srv is a forward simulation algorithm, which simulates DNA sequences assuming realistic models for human demographic and natural selection. 
  • ​Access point
  1. ​simupop: providing update information and download links. ​
  • Cite our paper
  1. Peng B and Liu X. 2011. Simulating Sequences of the Human Genome with Rare Variants. Human Heredity. 70(4): 287–291.
  • jPopGen Suite: jPopGen Suite is an user-friendly package of java programs for population genetic analysis of SNP spectrum data from randomly sampled DNA sequences.
  • Access point
  1. google sites: providing update information and download links. ​
  • ​​Cite our paper
  1. Liu X. 2012. jPopGen Suite: population genetic analysis of DNA polymorphism from nucleotide sequences with errors. Methods in Ecology and Evolution. 3: 624-627.
  • Stairway Plot: The stairway plot is a method for inferring detailed population demographic history using the site frequency spectrum (SFS) from DNA sequence data. It does not need a pre-defined population model and can be applied to hundreds of unphased sequences.
  • Access points
  1. ​GitHub: providing update information and download links. 
  2. google sites: providing update information and download links. 
  • Cite our papers
  1. Liu X and Fu YX. 2015. Exploring population size changes using SNP frequency spectra. Nature Genetics. 47(5):555-559.
  2. Liu X. 2020. Human prehistoric demography revealed by the polymorphic pattern of CpG transitions. Molecular Biology and Evolution. 37(9):2691-2698. 
  3. Liu X and Fu YX. 2020. Stairway Plot 2: demographic history inference with folded SNP frequency spectra. Genome Biology. 21:280. 
If you used Stairway Plot version 0.1-1.0, please cite 1. If you used Stairway Plot version 1.5, please cite 1 & 2. If you used Stairway Plot version 2, please cite 1 & 3. 

Office

3720 Spectrum Boulevard, Suite 304
Tampa, FL 33612

Telephone

813-974-9865

Email

xiaomingliu@usf.edu