Quantifying and Addressing Coverage Bias in Phone Surveys

2021 ◽  
Author(s):  
Elliott Collins
Keyword(s):  
Coverage Bias

Are Demographics Adequate Controls for Cell-Phone-Only Coverage Bias in Mass Communication Research?

2015 ◽  
Vol 92 (3) ◽  
pp. 723-743 ◽  
Author(s):  
Brendan R. Watson ◽  
Rodrigo Zamith ◽  
Sarah Cavanah ◽  
Seth C. Lewis
Keyword(s):  
Mass Communication ◽  
Cell Phone ◽  
Communication Research ◽  
Coverage Bias

scholarly journals Optimizing de novo genome assembly from PCR-amplified metagenomes

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6902 ◽  
Author(s):  
Simon Roux ◽  
Gareth Trubl ◽  
Danielle Goudeau ◽  
Nandita Nath ◽  
Estelle Couradeau ◽  
...  
Keyword(s):  
Genome Assembly ◽  
De Novo ◽  
Pcr Amplification ◽  
Error Rates ◽  
De Novo Genome Assembly ◽  
Low Input ◽  
Assembly Algorithm ◽  
Coverage Bias ◽  
Size Number ◽  
Assembly Pipeline

Background Metagenomics has transformed our understanding of microbial diversity across ecosystems, with recent advances enabling de novo assembly of genomes from metagenomes. These metagenome-assembled genomes are critical to provide ecological, evolutionary, and metabolic context for all the microbes and viruses yet to be cultivated. Metagenomes can now be generated from nanogram to subnanogram amounts of DNA. However, these libraries require several rounds of PCR amplification before sequencing, and recent data suggest these typically yield smaller and more fragmented assemblies than regular metagenomes. Methods Here we evaluate de novo assembly methods of 169 PCR-amplified metagenomes, including 25 for which an unamplified counterpart is available, to optimize specific assembly approaches for PCR-amplified libraries. We first evaluated coverage bias by mapping reads from PCR-amplified metagenomes onto reference contigs obtained from unamplified metagenomes of the same samples. Then, we compared different assembly pipelines in terms of assembly size (number of bp in contigs ≥ 10 kb) and error rates to evaluate which are the best suited for PCR-amplified metagenomes. Results Read mapping analyses revealed that the depth of coverage within individual genomes is significantly more uneven in PCR-amplified datasets versus unamplified metagenomes, with regions of high depth of coverage enriched in short inserts. This enrichment scales with the number of PCR cycles performed, and is presumably due to preferential amplification of short inserts. Standard assembly pipelines are confounded by this type of coverage unevenness, so we evaluated other assembly options to mitigate these issues. We found that a pipeline combining read deduplication and an assembly algorithm originally designed to recover genomes from libraries generated after whole genome amplification (single-cell SPAdes) frequently improved assembly of contigs ≥10 kb by 10 to 100-fold for low input metagenomes. Conclusions PCR-amplified metagenomes have enabled scientists to explore communities traditionally challenging to describe, including some with extremely low biomass or from which DNA is particularly difficult to extract. Here we show that a modified assembly pipeline can lead to an improved de novo genome assembly from PCR-amplified datasets, and enables a better genome recovery from low input metagenomes.

scholarly journals RGEN-seq For Highly Sensitive Amplification-free Screen Of Off-target Sites Of Gene Editors

2021 ◽  
Author(s):  
Alexander Kuzin ◽  
Brendan Redler ◽  
Jaya Onuska ◽  
Alexei Slesarev
Keyword(s):  
Target Detection ◽  
Dna Cleavage ◽  
Affinity Purification ◽  
Pcr Amplification ◽  
Detailed Comparison ◽  
Detection Methods ◽  
Guide Rnas ◽  
Coverage Bias ◽  
Biochemical Assays ◽  
Target Sites

Abstract Sensitive detection of off-target sites produced by gene editing nucleases is crucial for developing reliable gene therapy platforms. Although several biochemical assays for the characterization of nuclease off-target effects have been recently published, significant technical and methodological issues still remain.. Of note, existing methods rely on PCR amplification, tagging, and affinity purification which can introduce bias, contaminants, sample loss through handling, etc. Here we describe a sensitive, PCR-free next-generation sequencing method (RGEN-seq) for unbiased detection of double-stranded breaks generated by RNA-guided CRISPR-Cas9 endonuclease. Through use of novel sequencing adapters, the RGEN-Seq method saves time, simplifies workflow, and removes genomic coverage bias and gaps associated with PCR and/or other enrichment procedures. RGEN-seq is fully compatible with existing off-target detection software; moreover, the unbiased nature of RGEN-seq offers a robust foundation for relating assigned DNA cleavage scores to propensity for off-target mutations in cells. A detailed comparison of RGEN-seq with other off-target detection methods is provided using a previously characterized set of guide RNAs.

scholarly journals Evaluating coverage bias in next-generation sequencing of Escherichia coli

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0253440
Author(s):  
Samantha Gunasekera ◽  
Sam Abraham ◽  
Marc Stegger ◽  
Stanley Pang ◽  
Penghao Wang ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
De Novo ◽  
Fragment Size ◽  
Gc Content ◽  
Main Concern ◽  
Whole Genome ◽  
Assembly Quality ◽  
Coverage Bias

Whole-genome sequencing is essential to many facets of infectious disease research. However, technical limitations such as bias in coverage and tagmentation, and difficulties characterising genomic regions with extreme GC content have created significant obstacles in its use. Illumina has claimed that the recently released DNA Prep library preparation kit, formerly known as Nextera Flex, overcomes some of these limitations. This study aimed to assess bias in coverage, tagmentation, GC content, average fragment size distribution, and de novo assembly quality using both the Nextera XT and DNA Prep kits from Illumina. When performing whole-genome sequencing on Escherichia coli and where coverage bias is the main concern, the DNA Prep kit may provide higher quality results; though de novo assembly quality, tagmentation bias and GC content related bias are unlikely to improve. Based on these results, laboratories with existing workflows based on Nextera XT would see minor benefits in transitioning to the DNA Prep kit if they were primarily studying organisms with neutral GC content.

scholarly journals Optimizing de novo genome assembly from PCR-amplified metagenomes

2018 ◽  
Author(s):  
Simon Roux ◽  
Gareth Trubl ◽  
Danielle Goudeau ◽  
Nandita Nath ◽  
Estelle Couradeau ◽  
...  
Keyword(s):  
Genome Assembly ◽  
De Novo Assembly ◽  
De Novo ◽  
Pcr Amplification ◽  
Error Rates ◽  
De Novo Genome Assembly ◽  
Low Input ◽  
Assembly Algorithm ◽  
Coverage Bias ◽  
Assembly Pipeline

Background. Metagenomics has transformed our understanding of microbial diversity across ecosystems, with recent advances enabling de novo assembly of genomes from metagenomes. These metagenome-assembled genomes are critical to provide ecological, evolutionary, and metabolic context for all the microbes and viruses yet to be cultivated. Metagenomes can now be generated from nanogram to subnanogram amounts of DNA. However, these libraries require several rounds of PCR amplification before sequencing, and recent data suggest these typically yield smaller and more fragmented assemblies than regular metagenomes. Methods. Here we evaluate de novo assembly methods of 169 PCR-amplified metagenomes, including 25 for which an unamplified counterpart is available, to optimize specific assembly approaches for PCR-amplified libraries. We first evaluated coverage bias by mapping reads from PCR-amplified metagenomes onto reference contigs obtained from unamplified metagenomes of the same samples. Then, we compared different assembly pipelines in terms of assembly size (number of bp in contigs ≥ 10kb) and error rates to evaluate which are the best suited for PCR-amplified metagenomes. Results. Read mapping analyses revealed that the depth of coverage within individual genomes is significantly more uneven in PCR-amplified datasets versus unamplified metagenomes, with regions of high depth of coverage enriched in short inserts. This enrichment scales with the number of PCR cycles performed, and is presumably due to preferential amplification of short inserts. Standard assembly pipelines are confounded by this type of coverage unevenness, so we evaluated other assembly options to mitigate these issues. We found that a pipeline combining read deduplication and an assembly algorithm originally designed to recover genomes from libraries generated after whole genome amplification (single-cell SPAdes) frequently improved assembly of contigs ≥ 10kb by 10 to 100-fold for low input metagenomes. Conclusions. PCR-amplified metagenomes have enabled scientists to explore communities traditionally challenging to describe, including some with extremely low biomass or from which DNA is particularly difficult to extract. Here we show that a modified assembly pipeline can lead to an improved de novo genome assembly from PCR-amplified datasets, and enables a better genome recovery from low input metagenomes.

scholarly journals DiADeM: differential analysis via dependency modelling of chromatin interactions with robust generalized linear models

2019 ◽  
Author(s):  
Rafał Zaborowski ◽  
Bartek Wilczyński
Keyword(s):  
Generalized Linear Models ◽  
Linear Models ◽  
Standard Technique ◽  
Differential Analysis ◽  
Genomic Distance ◽  
Chromosome Conformation ◽  
Structure And Dynamics ◽  
Chromatin Interactions ◽  
Coverage Bias ◽  
Biochemical Technique

AbstractHigh throughput Chromosome Conformation Capture experiments have become the standard technique to assess the structure and dynamics of chromosomes in living cells. As any other sufficiently advanced biochemical technique, Hi-C datasets are complex and contain multiple documented biases, with the main ones being the non-uniform read coverage and the decay of contact coverage with genomic distance. Both of these effects have been studied and there are published methods that are able to normalize different Hi-C data to mitigate these biases to some extent. It is crucial that this is done properly, or otherwise the results of any comparative analysis of two or more Hi-C experiments are bound to be biased. In this paper we study both mentioned biases present in the Hi-C data and show that normalization techniques aimed at alleviating the coverage bias are at the same time exacerbating the problems with contact decay bias. We also postulate that it is possible to use generalized linear models to directly compare non-normalized data an that it is giving better results in identification of differential contacts between Hi-C matrices than using the normalized data.

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