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I am currently a Postdoctoral Fellow with Eleazar Eskin (Department of Computer Science) at  UCLA. I am holding Collaboratory Fellowship from Institute for Quantitative and Computational Biosciences (QCB).

My research focuses on developing techniques to solve the challenging computational problems that arise in attempting to understand the genetic basis of human disease. Current projects primarily focus on understanding the functional mechanisms underlying the connection between the immune system and disease etiology.

My code. My twitter

News:

  • News! Slides from my talk at ASHG 2017 are online.
  • News! Slides from my talk at [BC]2 2017 are online.
  • News! Slides from my talk at Workshop on Benchmarking: Incentives and Best Practices across Scientific Disciplines ([BC]2 2017) are online.
  • New preprint! Our preprint about best practices for conducting benchmarking in the most comprehensive and reproducible way is online at PeerJ Preprints [preprint]
  • New preprint! Our preprint about involving undergraduates in genomics research to narrow the education-research gap is online at PeerJ Preprints [preprint] [resources]
  • New paper! Our new paper “Addressing the digital divide in contemporary biology: Lessons from teaching UNIX” is published in Trends in Biotechnology (Cell press). It was the top tweeted story in bioinformatics (according to https://twitter.com/rnomics). [paper] [preprint] [teaching materials] [resources]
  • News! Slides from my talk at ISMB 2017 (HiTSeq 2017) are online.
  • News! Slides from my talk at ISMB 2017 workshop on Critical Assessment of Massive Data Analysis (CAMDA 2017) are online.
  • New release! New release of ROP (v1.0.7) is available here. ROP now accepts a mixture of mapped and unmapped reads (in bam file) to profile immune repertoires. We have added  ggprofilePlus.py to randomly assign multi-mapped reads into genomic categories considering estimated gene expression levels.
  • New software! We released UMI-Reducer : a computational method allowing to differentiate  PCR duplicates from biological duplicates based on the UMIs (U nique Molecular Identifiers). This is a collaboration with Kelsey Martin Lab. Details about the tool are available in biorxiv  preprint
  • New release! New release of ROP (v1.0.6) is available here.We have switched from IgBLAST to ImReP to profile B and T cell receptor repertoires.  ImReP shows superior accuracy compared to existing tools  (see our manuscript “Profiling adaptive immune repertoires across multiple human tissues by RNA Sequencing” available at bioRxiv).
  • New release! New release of ImReP (v0.3) is available here. The various options have been added. A detailed tutorial is available here. Toy example with simulated receptor-derived reads is now distributed with the tool.
  • News! Slides from my talk at PSB 2017 workshop on Open Data for Discovery Science  are online
  • New release! New release of ImReP (v0.2) is available here.  A detailed tutorial is available here.
  • New software! We released ImReP :  a novel computational method for rapid and accurate profiling of the adaptive immune repertoire from regular RNA-Seq data.  ImReP is able to quantify individual immune responses based on a recombination landscape of genes encoding B and T cell receptors.
  • New preprint! Our paper about  immune repertoires profiling from RNA-Seq across 53 various GTEx tissues is online at bioRxiv [preprint] [software]
  • New paper! Discovering SNPs Regulating Human Gene Expression Using Allele Specific Expression from RNA-Seq Data. Genetics [paper] [blog] [software]
  • News! Slides from my talk at ASHG 2016 are online.
  • News! Slides from my talk at Workshop on Computational Challenges of Third Generation DNA Sequencing Data Analysis (ECCB 2016) are online.
  • New release! New release of the ROP (v 1.0.5) is available here. Thanks to contributions from Jeremy Rotman, Benjamin Statz, William Van Der Wey, Kevin Wesel at Bruins-In-Genomics (B.I.G.) Summer Program . Special thanks for Linus Chen and Kevin Hsieh for improving the code and developing ROP-mouse.
  • New release! New release of ROP (v 1.0.4) is available here.  Now we accept more formats (.fastq, bam, fasta, fastq.gz). ROP now is using a custom script to identify low-quality reads.
  • Journal Club!  I am leading the Journal Club about the interactions of microbiome and immune system.We will be discussing how to study the interactions of microbiome and immune system and how both are effected by genetics. Also we will be discussing the methods devoted to study the immune system and microbiome.  More details here.
  • UNIX Online Tutorial! We present three video recordings of workshops developed under the UCLA Institute for Quantitative and Computational Biosciences. Workshop provides just enough information for students with no computational background to get started using Unix for analytical tasks.
  • New release! New release of the ROP (v 1.0.3) is available here.  It includes new options and improvements. The list of the tools, parameters and reference databases  used by the ROP is now saved to a log file. More details here.
  • New preprint! Our paper about microbial communities in human blood and disease specific effects is online at bioRxiv [preprint] [in the news] [scientific digest]
  • New preprint! Our paper on how to compare microbial communities with no reference is online atbioRxiv [preprint]
  • New paper! Our paper about haplotype phasing of the transcriptome is online at Lecture Notes in Computer Science (accepted as ISBRA 2016) [paper] [preprint]
  • New release! New release of the ROP (v 1.0.2) is available here.  ROP 1.0.2 is a maintenance release with the minor changes.
  • New release! New release of the ROP (v 1.0.1) is available here. The functionality to run the targeted analysis for your samples been added. For example you can run antibody profiling for your data skipping all other steps. The current release also allows ROP to accept the input (unmapped reads) in the .bam and .fastq.gz formats
  • New software! We released ROP : read origin protocol! ROP is a computational protocol aimed to discover the source of all (98.8%) reads, originated from complex RNA molecules, recombinant antibodies and microbial communities.   ROP profiles repeats, circRNAs, gene fusions, trans-splicing events, recombined B and T cell receptors and microbial communities.
  • New paper! Our paper on assembling rare and closely related mutant variants from long single molecule reads is online at Lecture Notes in Computer Science (accepted as RECOMB 2016) [paper] [preprint]
  • New tutorial! Our tutorial “Human Microbiome Analysis: Computational Techniques and Challenges”  was accepted for BC2 conference
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