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Jafar S. Jabbari on Muck Rack

Jafar S. Jabbari

As seen in: Nature, Genome Biology, BioRxiv, Genome Research
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Articles

Single-cell Rapid Capture Hybridization sequencing reliably detects isoform usage and coding mutations in targeted genes

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By Hongke Peng, Jafar S. Jabbari, Luyi Tian, Changqing Wang
| Genome Research
1,2,6,7,8 1The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia; 2Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia; 3Monash Haematology, Monash Health, Melbourne 3168, Australia; 4Clinical Haematology, Northern Health, Melbourne 3076, Australia; 5Department of Clinical Haematology, Royal Melbourne Hospital and Peter MacCallum Cancer Centre, Melbourne 3052, Australia; 6Department of Hematology, Amsterdam UMC, Amsterdam 1081HV, the...
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Single-cell Rapid Capture Hybridization sequencing (scRaCH-seq) to reliably detect isoform usage and coding mutations in targeted genes at a single-cell level

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By Jafar S. Jabbari, Luyi Tian, Chong Chyn Chua, Hongke Peng
| BioRxiv
Abstract Single-cell long-read sequencing has transformed our understanding of isoform usage and the mutation heterogeneity between cells. Despite unbiased in-depth analysis, the low sequencing throughput often results in insufficient read coverage thereby limiting our ability to perform mutation calling for specific genes.
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Benchmarking long-read RNA-sequencing analysis tools using in silico mixtures - Nature Methods

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By Xueyi Dong, Quentin Gouil, Jafar S. Jabbari, Pedro L. Baldoni, Yunshun Chen, Gordon K. Smyth, Rory Bowden
| Nature Verified
Abstract The lack of benchmark data sets with inbuilt ground-truth makes it challenging to compare the performance of existing long-read isoform detection and differential expression analysis workflows. Here, we present a benchmark experiment using two human lung adenocarcinoma cell lines that were each profiled in triplicate together with synthetic, spliced, spike-in RNAs (sequins). Samples were deeply sequenced on both Illumina short-read and Oxford Nanopore Technologies long-read platforms.
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