Biology subjects

Ali Torkamani

Publications and source records attributed to Ali Torkamani.

4 recordsLinked to original sources

bioRxiv2016

A Whole Blood Molecular Signature for Acute Myocardial Infarction

Chest pain is a leading reason patients seek medical evaluation. While assays to detect myocyte death are used to diagnose a heart attack (acute myocardial infarction, AMI), there is no biomarker to indicate an impending cardiac event. Transcriptional patterns present in circulating endothelial cells (CEC) may provide a window into the plaque rupture process and identify a proximal biomarker for AMI. Thus, we aimed to identify a transcriptomic signature of AMI present in whole blood, but derived from CECs. Candidate genes indicative of AMI were nominated from microarray of enriched CEC samples, and then verified for detectability and predictive potential via qPCR in whole blood. This signature was validated in an independent cohort. Our findings suggest that a whole blood CEC-derived molecular signature identifies patients with AMI and sets the framework to potentially identify the earlier stages of an impending cardiac event where conventional biomarkers indicative of myonecrosis remain undetected.\n\nABBREVIATIONS

Genomics↗

bioRxiv2016

Assessment of Circulating Copy Number Variant Detection for Cancer Screening

Current high-sensitivity cancer screening methods suffer from false positive rates that lead to numerous unnecessary procedures and questionable public health benefit overall. Detection of circulating tumor DNA (ctDNA) has the potential to transform cancer screening. Thus far, nearly all ctDNA studies have focused on detection of tumor-specific point mutations. However, ctDNA point mutation detection methods developed to date lack either the scope or sensitivity necessary to be useful for cancer screening, due to the extremely low (<1%) ctDNA fraction derived from early stage tumors. We suggest that tumor-derived copy number variant (CNV) detection is theoretically a superior means of ctDNA-based cancer screening for many tumor types, given that, relative to point mutations, each individual tumor CNV contributes a much larger number of ctDNA fragments to the overall pool of circulating DNA. Here we perform an in silico assessment of the potential for ctDNA CNV-based cancer screening across many common cancers.

Bioinformatics↗

bioRxiv2016

RASLseqTools: open-source methods for designing and analyzing RNA-mediated oligonucleotide Annealing, Selection, and, Ligation sequencing (RASL-seq) experiments

RNA-mediated oligonucleotide Annealing, Selection, and Ligation (RASL-seq) is a method to measure the expression of hundreds of genes in thousands of samples for a fraction of the cost of competing methods. However, enzymatic inefficiencies of the original protocol and the lack of open source software to design and analyze RASL-seq experiments have limited its widespread adoption. We recently reported an Rnl2-based RASL-seq protocol (RRASL-seq) that offers improved ligation efficiency and a probe decoy strategy to optimize sequencing usage. Here, we describe an open source software package, RASLseqTools, that provides computational methods to design and analyze RASL-seq experiments. Furthermore, using data from a large RRASL-seq experiment, we demonstrate how normalization methods can be used for characterizing and correcting experimental, sequencing, and alignment error. We provide evidence that the three principal predictors of RRASL-seq reproducibility are barcode/probe sequence dissimilarity, sequencing read depth, and normalization strategy. Using dozens of technical and biological replicates across multiple 384-well plates, we find simple normalization strategies yield similar results to more statistically complex methods.

Bioinformatics↗

bioRxiv2015

MyGene.info and MyVariant.info: Gene and Variant Annotation Query Services

MyGene.info and MyVariant.info provide high-performance data APIs for querying gene and variant annotation information. They demonstrate a new model for organizing biological annotation information by utilizing a cloud-based scalable infrastructure. MyGene.info and MyVariant.info can be accessed at http://mygene.info and http://myvariant.info.

Bioinformatics↗