clustering amplicons  (Pyrosequencing Inc)

Journal: bioRxiv

Article Title: AmpliCI: A High-resolution Model-Based Approach for Denoising Illumina Amplicon Data

doi: 10.1101/2020.02.23.961227

Figure Lengend Snippet: AmpliCI: inferring ASVs from samples. 1) A hash index is applied to construct the unique sequence set S, and the haplotype set contains the most abundant unique sequence. 2) Given the current haplotype set , the scaled abundances are estimated for each remaining unique sequence s m via update function , and the haplotype candidate with the highest scaled abundance is selected. 3) Test if the diagnostic probability is smaller than the given threshold and the approximate Bayesian Information Criterion (BIC) improves. If the haplotype is discarded, we select the next most abundant candidate. Otherwise, add candidate s m to the current haplotype set, . 4) repeat 2) - 3) until the scaled abundance of all remaining unique sequences are below the user-determined lower bound c . 5) Output the haplotype set with K haplotypes.

Article Snippet: We introduce AmpliCI, Amplicon Clustering Inference, a model-based algorithm for denoising Illumina amplicon data.

Techniques: Construct, Sequencing, Diagnostic Assay

Journal: bioRxiv

Article Title: AmpliCI: A High-resolution Model-Based Approach for Denoising Illumina Amplicon Data

doi: 10.1101/2020.02.23.961227

Figure Lengend Snippet:

Article Snippet: We introduce AmpliCI, Amplicon Clustering Inference, a model-based algorithm for denoising Illumina amplicon data.

Techniques: Amplification, Generated

Journal: bioRxiv

Article Title: AmpliCI: A High-resolution Model-Based Approach for Denoising Illumina Amplicon Data

doi: 10.1101/2020.02.23.961227

Figure Lengend Snippet: Mean proportion of detected haplotypes ± standard error for six levels of simulated haplotype similarity. For each level, the x coordinate is set to the mean haplotype similarity of the three simulated datasets. When the similarity level among haplotypes increases, AmpliCI performs better than competing methods. Detailed results on each dataset are provided in Supplementary Table S1.

Article Snippet: We introduce AmpliCI, Amplicon Clustering Inference, a model-based algorithm for denoising Illumina amplicon data.

Techniques:

Journal: bioRxiv

Article Title: AmpliCI: A High-resolution Model-Based Approach for Denoising Illumina Amplicon Data

doi: 10.1101/2020.02.23.961227

Figure Lengend Snippet: Venn diagrams of haplotypes discovered in the vaginal microbiome dataset by AmpliCI, AmpliCI-con, DADA2, UNOISE3, and Deblur. Haplotypes with a 100% match to the Silva v132 rRNA gene database are shaded. AmpliCI and AmpliCI-con compared to (a) DADA2 with abundance threshold c = 2, (b) UNOISE3 with c = 2 and cross-sample abundance threshold c * = 8, (c) Deblur with c = 2 and cross-sample abundance threshold c * = 10.

Article Snippet: We introduce AmpliCI, Amplicon Clustering Inference, a model-based algorithm for denoising Illumina amplicon data.

Techniques:

Journal: Current opinion in genetics & development

Article Title: Satellite DNA evolution: old ideas, new approaches

doi: 10.1016/j.gde.2018.03.003

Figure Lengend Snippet: Technological strategies for assessing satellite DNA

Article Snippet: Illumina , Up to 300 bp; clustered amplicon , Inexpensive, low error rate , PCR bias in library prep * ; short reads , [ 40 ].

Techniques: Amplification, High Molecular Weight, Sequencing

Journal: Current opinion in genetics & development

Article Title: Satellite DNA evolution: old ideas, new approaches

doi: 10.1016/j.gde.2018.03.003

Figure Lengend Snippet: Software for assessing satellite DNA This table is not comprehensive. We focus on recently developed assembly-free methods for analysis of large tandem arrays (excluding microsatellites). We also include more widely used methods for assessing tandem repeats in genome assemblies (i) as a comparison to methods designed specifically for assembly-free data, (ii) because some can also be applied to unassembled long reads (as long as the repeat monomers are shorter than the read length), and (iii) because they will continue to prove useful as improved read lengths enable assembly of satellite arrays.

Article Snippet: However, assessing variation in satellite sequence and abundance using these methods requires stringent filtering and validation methods to account for their high error rates. table ft1 table-wrap mode="anchored" t5 caption a7 Platform Read length; method Pros Cons Example Illumina Up to 300 bp; clustered amplicon Inexpensive, low error rate PCR bias in library prep * ; short reads [ 40 ] Ion torrent Up to 400 bp; on-bead amplicon Fast, inexpensive Lower yield; high error rate in homopolymer tracts [ 27 ] Pacific Biosciences Up to 50 kb; single molecule Long reads; can assemble complex satellite regions Expensive; high error rate ** [ 5 ] Oxford Nanopore Up to 300 kb; single molecule Longest reads High error rate; extracting high molecular weight DNA is limiting Jain et al., bioRxiv 10.1101/170373 Optical mapping (nanochannel) Up to 220 kb; single molecule Long-range positional information; orthogonal method to sequencing Requires a reference genome; large nicking intervals preclude mapping simple sequences [ 41 ] Open in a separate window * PCR-free libraries reduce bias.

Techniques: Software, Comparison, Sequencing, Variant Assay, Biomarker Discovery

Journal: Current opinion in genetics & development

Article Title: Satellite DNA evolution: old ideas, new approaches

doi: 10.1016/j.gde.2018.03.003

Figure Lengend Snippet: Technological strategies for assessing satellite DNA

Article Snippet: However, assessing variation in satellite sequence and abundance using these methods requires stringent filtering and validation methods to account for their high error rates. table ft1 table-wrap mode="anchored" t5 caption a7 Platform Read length; method Pros Cons Example Illumina Up to 300 bp; clustered amplicon Inexpensive, low error rate PCR bias in library prep * ; short reads [ 40 ] Ion torrent Up to 400 bp; on-bead amplicon Fast, inexpensive Lower yield; high error rate in homopolymer tracts [ 27 ] Pacific Biosciences Up to 50 kb; single molecule Long reads; can assemble complex satellite regions Expensive; high error rate ** [ 5 ] Oxford Nanopore Up to 300 kb; single molecule Longest reads High error rate; extracting high molecular weight DNA is limiting Jain et al., bioRxiv 10.1101/170373 Optical mapping (nanochannel) Up to 220 kb; single molecule Long-range positional information; orthogonal method to sequencing Requires a reference genome; large nicking intervals preclude mapping simple sequences [ 41 ] Open in a separate window * PCR-free libraries reduce bias.

Techniques: Amplification, High Molecular Weight, Sequencing