Biology subjects

Zamin Iqbal

Publications and source records attributed to Zamin Iqbal.

7 recordsLinked to original sources

bioRxiv2016

Using reference-free compressed data structures to analyse sequencing reads from thousands of human genomes

We are rapidly approaching the point where we have sequenced millions of human genomes. There is a pressing need for new data structures to store raw sequencing data and efficient algorithms for population scale analysis. Current reference based data formats do not fully exploit the redundancy in population sequencing nor take advantage of shared genetic variation. In recent years, the Burrows-Wheeler transform (BWT) and FM-index have been widely employed as a full text searchable index for read alignment and de novo assembly. We introduce the concept of a population BWT and use it to store and index the sequencing reads of 2,705 samples from the 1000 Genomes Project. A key feature is that as more genomes are added, identical read sequences are increasingly observed and compression becomes more efficient. We assess the support in the 1000 Genomes read data for every base position of two human reference assembly versions, identifying that 3.2 Mbp with population support was lost in the transition from GRCh37 with 13.7 Mbp added to GRCh38. We show that the vast majority of variant alleles can be uniquely described by overlapping 31-mers and show how rapid and accurate SNP and indel genotyping can be carried out across the genomes in the population BWT. We use the population BWT to carry out non-reference queries to search for the presence of all known viral genomes, and discover human T-lymphotropic virus 1 integrations in six samples in a recognised epidemiological distribution.

Genomics↗

bioRxiv2016

A natural encoding of genetic variation in a Burrows-Wheeler Transform to enable mapping and genome inference

We show how positional markers can be used to encode genetic variation within aBurrows-Wheeler Transform (BWT), and use this to construct a generalisation ofthe traditional \"reference genome\", incorporating known variation within aspecies. Our goal is to support the inference of the closest mosaic of previouslyknown sequences to the genome(s) under analysis.\n\nOur scheme results in an increased alphabet size, and by using a wavelet tree encoding of the BWT we reduce the performance impact on rank operations. We give a specialised form of the backward search that allows variation-aware exact matching. We implement this, and demonstrate the cost of constructing an index of the whole human genome with 8 million genetic variants is 25GB of RAM. We also show that inferring a closer reference can close large kilobase-scale coverage gaps in P. falciparum.

Bioinformatics↗

bioRxiv2016

A reference dataset of 5.4 million phased human variants validated by genetic inheritance from sequencing a three-generation 17-member pedigree

Improvement of variant calling in next-generation sequence data requires a comprehensive, genome-wide catalogue of high-confidence variants called in a set of genomes for use as a benchmark. We generated deep, whole-genome sequence data of seventeen individuals in a three-generation pedigree and called variants in each genome using a range of currently available algorithms. We used haplotype transmission information to create a phased \"platinum\" variant catalogue of 4.7 million single nucleotide variants (SNVs) plus 0.7 million small (1-50bp) insertions and deletions (indels) that are consistent with the pattern of inheritance in the parents and eleven children of this pedigree. Platinum genotypes are highly concordant with the current catalogue of the National Institute of Standards and Technology for both SNVs (>99.99%) and indels (99.92%), and add a validated truth catalogue that has 26% more SNVs and 45% more indels. Analysis of 334,652 SNVs that were consistent between informatics pipelines yet inconsistent with haplotype transmission (\"non-platinum\") revealed that the majority of these variants are de novo and cell-line mutations or reside within previously unidentified duplications and deletions. The reference materials from this study are a resource for objective assessment of the accuracy of variant calls throughout genomes.

Bioinformatics↗

bioRxiv2015

High-accuracy HLA type inference from whole-genome sequencing data

Extensive hyperpolymorphism and sequence similarity between the HLA genes make HLA type inference from whole-genome sequencing data a challenging problem. We address these by representing sequences from over 10,000 known alleles in a reference graph structure, enabling accurate read mapping. HLA*PRG, our algorithm, outperforms existing methods by a wide margin and for the first time consistently achieves the accuracy of gold-standard reference methods with one error across 158 alleles tested.

Bioinformatics↗

bioRxiv2015

Genome variation and meiotic recombination in Plasmodium falciparum: insights from deep sequencing of genetic crosses

The malaria parasite Plasmodium falciparum has a great capacity for evolutionary adaptation to evade host immunity and develop drug resistance. Current understanding of parasite evolution is impeded by the fact that a large fraction of the genome is either highly repetitive or highly variable, and thus difficult to analyse using short read technologies. Here we describe a resource of deep sequencing data on parents and progeny from genetic crosses, which has enabled us to perform the first genome-wide, integrated analysis of SNP, INDEL and complex polymorphisms, using Mendelian error rates as an indicator of genotypic accuracy. These data reveal that INDELs are exceptionally abundant, being more common than SNPs and thus the dominant mode of polymorphism within the core genome. We use the high density of SNP and INDEL markers to analyse patterns of meiotic recombination, confirming a high rate of crossover events, and providing the first estimates for the rate of non-crossover events and the length of conversion tracts. We observe several instances of recombination that modify copy number variants associated with drug resistance, demonstrating a mechanism whereby fitness costs associated with resistance mutations could be compensated and greater phenotypic plasticity could be acquired. We describe a novel web application that allows these data to be explored in detail.

Genomics↗

bioRxiv2015

Rapid antibiotic resistance predictions from genome sequence data for S. aureus and M. tuberculosis.

Rapid and accurate detection of antibiotic resistance in pathogens is an urgent need, affecting both patient care and population-scale control. Microbial genome sequencing promises much, but many barriers exist to its routine deployment. Here, we address these challenges, using a de Bruijn graph comparison of clinical isolate and curated knowledge-base to identify species and predict resistance profile, including minor populations. This is implemented in a package, Mykrobe predictor, for S. aureus and M. tuberculosis, running in under three minutes on a laptop from raw data. For S. aureus, we train and validate in 495/471 samples respectively, finding error rates comparable to gold-standard phenotypic methods, with sensitivity/specificity of 99.3%/99.5% across 12 drugs. For M. tuberculosis, we identify species and predict resistance with specificity of 98.5% (training/validating on 1920/1609 samples). Sensitivity of 82.6% is limited by current understanding of genetic mechanisms. Finally, we demonstrate feasibility of an emerging single-molecule sequencing technique.

Genomics↗

bioRxiv2014

Improved genome inference in the MHC using a population reference graph

In humans and many other species, while much is known about the extent and structure of genetic variation, such information is typically not used in assembling novel genomes. Rather, a single reference is used against which to map reads, which can lead to poor characterisation of regions of high sequence or structural diversity. Here, we introduce a population reference graph, which combines multiple reference sequences as well as catalogues of SNPs and short indels. The genomes of novel samples are reconstructed as paths through the graph using an efficient hidden Markov Model, allowing for recombination between different haplotypes and variants. By applying the method to the 4.5Mb extended MHC region on chromosome 6, combining eight assembled haplotypes, sequences of known classical HLA alleles and 87,640 SNP variants from the 1000 Genomes Project, we demonstrate, using simulations, SNP genotyping, short-read and longread data, how the method improves the accuracy of genome inference. Moreover, the analysis reveals regions where the current set of reference sequences is substantially incomplete, particularly within the Class II region, indicating the need for continued development of reference-quality genome sequences.

Genomics↗