arXiv subjects

Zamin Iqbal

Publications and source records attributed to Zamin Iqbal.

4 recordsLinked to original sources

arXiv2019

COBS: a Compact Bit-Sliced Signature Index

We present COBS, a COmpact Bit-sliced Signature index, which is a cross-over between an inverted index and Bloom filters. Our target application is to index $k$-mers of DNA samples or $q$-grams from text documents and process approximate pattern matching queries on the corpus with a user-chosen coverage threshold. Query results may contain a number of false positives which decreases exponentially with the query length. We compare COBS to seven other index software packages on 100000 microbial DNA samples. COBS' compact but simple data structure outperforms the other indexes in construction time and query performance with Mantis by Pandey et al. in second place. However, unlike Mantis and other previous work, COBS does not need the complete index in RAM and is thus designed to scale to larger document sets.

cs.DB↗

arXiv2016

Identifying lineage effects when controlling for population structure improves power in bacterial association studies

Bacteria pose unique challenges for genome-wide association studies (GWAS) because of strong structuring into distinct strains and substantial linkage disequilibrium across the genome. While methods developed for human studies can correct for strain structure, this risks considerable loss- of-power because genetic differences between strains often contribute substantial phenotypic variability. Here we propose a new method that captures lineage-level associations even when locus-specific associations cannot be fine-mapped. We demonstrate its ability to detect genes and genetic variants underlying resistance to 17 antimicrobials in 3144 isolates from four taxonomically diverse clonal and recombining bacteria: Mycobacterium tuberculosis, Staphylococcus aureus, Escherichia coli and Klebsiella pneumoniae. Strong selection, recombination and penetrance confer high power to recover known antimicrobial resistance mechanisms, and reveal a candidate association between the outer membrane porin nmpC and cefazolin resistance in E. coli. Hence our method pinpoints locus-specific effects where possible, and boosts power by detecting lineage-level differences when fine-mapping is intractable.

q-bio.GN↗

arXiv2015

An integrative statistical model for inferring strain admixture within clinical Plasmodium falciparum isolates

Since the arrival of genetic typing methods in the late 1960's, researchers have puzzled at the clinical consequence of observed strain mixtures within clinical isolates of Plasmodium falciparum. We present a new statistical model that infers the number of strains present and the amount of admixture with the local population (panmixia) using whole-genome sequence data. The model provides a rigorous statistical approach to inferring these quantities as well as the proportions of the strains within each sample. Applied to 168 samples of whole-genome sequence data from northern Ghana, the model provides significantly improvement fit over models implementing simpler approaches to mixture for a large majority (129/168) of samples. We discuss the possible uses of this model as a window into within-host selection for clinical and epidemiological studies and outline possible means for experimental validation.

stat.AP↗

arXiv2013

A Bayesian approach to inferring the phylogenetic structure of communities from metagenomic data

Metagenomics provides a powerful new tool set for investigating evolutionary interactions with the environment. However, an absence of model-based statistical methods means that researchers are often not able to make full use of this complex information. We present a Bayesian method for inferring the phylogenetic relationship among related organisms found within metagenomic samples. Our approach exploits variation in the frequency of taxa among samples to simultaneously infer each lineage haplotype, the phylogenetic tree connecting them, and their frequency within each sample. Applications of the algorithm to simulated data show that our method can recover a substantial fraction of the phylogenetic structure even in the presence of strong mixing among samples. We provide examples of the method applied to data from green sulfur bacteria recovered from an Antarctic lake, plastids from mixed Plasmodium falciparum infections, and virulent Neisseria meningitidis samples.

q-bio.QM↗