Naser Ansari-Pour
@NaserAnsariPour
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Lead Genomic Data Scientist at @OUHospitals (formerly at @UniofOxford); Dad of 3
Oxford, England
Joined December 2019
Curious in what drives relapse/refractory myeloma (rrMM) at the genomic level? Have a look at our paper published @BloodJournal reporting the largest deep WGS dataset to date. Great transatlantic team effort @mksamur @DrSarahGooding ... & Anjan Thakurta #myeloma #CancerResearch
Whole-genome analysis identifies novel drivers and high-risk double-hit events in relapsed/refractory myeloma https://t.co/HLnuvYUZ6p
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Our paper on detecting and quantifying clonal selection from a single bulk sequencing sample is out! This was a great collaboration with @pvyas_oxford, Thomas Höfer, @asger_jakobsen and @NaserAnsariPour. Read the full story here: https://t.co/bpA30Lyy9Q
nature.com
Nature Genetics - SCIFER detects clonal selection in whole-genome sequencing data using a population genetics model. Applied to a range of somatic tissues, SCIFER quantifies stem cell dynamics and...
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Just saw our paper on my Google News Feed! Nice 👌🏼
Our paper on detecting and quantifying clonal selection from a single bulk sequencing sample is out! This was a great collaboration with @pvyas_oxford, Thomas Höfer, @asger_jakobsen and @NaserAnsariPour. Read the full story here: https://t.co/bpA30Lyy9Q
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Cancer origin tracing and timing in two high-risk prostate cancers using multisample whole genome analysis: prospects for personalized medicine. #BeyondTheAbstract on UroToday > https://t.co/ifjV2udKg9
@TVisakorpi @Tmurtola @NaserAnsariPour
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My annual reminder to please stop using Tophat. Still papers using Tophat v1 (!) from 12 years ago 😱 There have been many better alternatives around for a long time now. Screenshot below is from https://t.co/OHCTVI9q53
Please stop using Tophat https://t.co/Es4ohxOEyx Cole and I developed the method in *2008*. It was greatly improved in TopHat2 then HISAT & HISAT2. There is no reason to use it anymore. I have been saying this for years yet it has more citations this year than last #methodsmatter
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A significant step in the right direction for mutational signature analysis. I was always suspicious of SBS39 and we even touched upon this in our paper ( https://t.co/5cvfIiyDOu; see excerpt from the paper) due to its high similarity to SBS3!
Mutational signature analysis has become a key tool for interpreting somatic mutations. Our tool MuSiCal (Mutational Signature Calculator) by the amazing Hu Jin (@hujin2hujin2) and Doga Gulhan (@dcgulhan) is out at Nat Genetics: https://t.co/8Cy6dWmhPa. Three key ideas below.
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Mutational signature analysis has become a key tool for interpreting somatic mutations. Our tool MuSiCal (Mutational Signature Calculator) by the amazing Hu Jin (@hujin2hujin2) and Doga Gulhan (@dcgulhan) is out at Nat Genetics: https://t.co/8Cy6dWmhPa. Three key ideas below.
nature.com
Nature Genetics - MuSiCal is a mutational signature analysis tool combining minimum-volume nonnegative matrix factorization with other algorithmic innovations. Applied to PCAWG data, MuSiCal gives...
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💭Can we learn the lessons of the personalised medicine revolution in solid cancers to improve treatment of multiple myeloma? We must, says clinician scientist Dr Sarah Gooding. @DrSarahGooding | @MRC_WIMM | @MRC_MHU | @OxfordHaem Read more: https://t.co/gsWYD364DA
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#MachineLearning clinical prediction models fail to generalize across trial data, a new Science study finds. The results "require reexamination of the practical challenges that precision medicine is facing." https://t.co/uJQxABQdH1
#SciencePerspective: https://t.co/FnWo477PLH
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New article: Whole-genome analysis identifies novel drivers and high-risk double-hit events in relapsed/refractory myeloma https://t.co/N8lluzEl4S
#MMSM #MultipleMyeloma #hematology
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Our relapsed/refractory myeloma whole genome paper is now out! @NaserAnsariPour @mksamur … and thanks for the editorial @alagana1
@MRC_WIMM @MRC_MHU
Whole-genome analysis identifies novel drivers and high-risk double-hit events in relapsed/refractory myeloma https://t.co/HLnuvYUZ6p
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For a quick overview of our deep WGS rrMM paper (N=418), have a look at this fantastic editorial @BloodJournal. Thanks @alagana1! https://t.co/fuhfrEZpis
Whole-genome analysis identifies novel drivers and high-risk double-hit events in relapsed/refractory myeloma https://t.co/HLnuvYUZ6p
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Our main findings are: BRAFⱽ⁶⁰⁰ᴱ acts either alone or conjointly with 1 or 2 additional mutational drivers to initiate and promote malignant transformation AND Subsequent subclonal diversification occurs with some driven only by copy number aberrations (CNA).
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The first whole genome sequencing (WGS)-based evolutionary trajectory analysis of classical hairy cell leukaemia is now published @LeukemiaJnl ( https://t.co/TeKacvoSLC). Proud to have jointly supervised this work along with Surinder S Sahota @UoS_Medicine.
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Get in touch if you’re interested! Great science, friendly and supportive lab, important topics…
Check out this Research Assistant role in the Chapman Group working with @DrSarahGooding! @Chapman_lab_UK use cutting edge molecular techniques to better understand how faulty DNA repair and genome instability shape multiple myeloma. Find out more➡️ https://t.co/X7YTTmhNmU
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We have identified interesting enrichment patterns which provide crucial insight into the genetics of how #myeloma tumours become therapeutically resistant. A tweetorial will follow soon! Thanks to all authors, especially Anjan Thakurta who made this happen! #BeatCancer
@MRC_WIMM
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Interested in the genomic features driving relapse/refractory #MultipleMyeloma? Super pleased that my analysis of the largest rrMM deep whole-genome sequencing dataset (N=418 tumours) is now published in @BloodJournal ( https://t.co/MDg0QatGJG).
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