#ashg24 — Public Fediverse posts

PacificBiosciences/HiFi-SVTopo: Complex structural variant visualization for HiFi sequencing data github.com/PacificBiosc... ...being presented at #ashg24 this year. 🧬🖥️

PacificBiosciences/HiFi-SVTopo: Complex structural variant visualization for HiFi sequencing data github.com/PacificBiosc... ...being presented at #ashg24 this year. 🧬🖥️

PacificBiosciences/HiFi-SVTopo: Complex structural variant visualization for HiFi sequencing data github.com/PacificBiosc... ...being presented at #ashg24 this year. 🧬🖥️

PacificBiosciences/HiFi-SVTopo: Complex structural variant visualization for HiFi sequencing data github.com/PacificBiosc... ...being presented at #ashg24 this year. 🧬🖥️

Continued 2: GDS: Mendelian randomization design: Z → X → Y ← C Z: genetic variant C: confounder X: exposure of interest Y: outcome #ASHG24 🧪🧬🖥️

Not actually #ASHG24. Anyway, continuing on. #

GS: Mendelian randomization introduced because of the dramatic failure of other attempts to find causality from observational methods. #ASHG24

Now: @mendelrandom.bsky.social (GS): Mendelian randomization: what it was, what it is, and what it should become #ASHG24 🧪🧬🖥️

NEWS! Check our wrap-up about #ashg24 https://shorturl.at/WcTiz

Something is missing? Let us know!

🙌 Thanks, ASHG, for giving us the floor to share updates with #genetics community, delivered by our colleague @mariacerezo.bsky.social

#OpenAccess #gwas #gwasdatahero

Stronger together @ebi.embl.org @NIH

NEWS! Check our wrap-up about #ashg24 https://shorturl.at/WcTiz

Something is missing? Let us know!

🙌 Thanks, ASHG, for giving us the floor to share updates with #genetics community, delivered by our colleague @mariacerezo.bsky.social

#OpenAccess #gwas #gwasdatahero

Stronger together @ebi.embl.org @NIH

NEWS! Check our wrap-up about #ashg24 https://shorturl.at/WcTiz

Something is missing? Let us know!

🙌 Thanks, ASHG, for giving us the floor to share updates with #genetics community, delivered by our colleague @mariacerezo.bsky.social

#OpenAccess #gwas #gwasdatahero

Stronger together @ebi.embl.org @NIH

NEWS! Check our wrap-up about #ashg24 https://shorturl.at/WcTiz

Something is missing? Let us know!

🙌 Thanks, ASHG, for giving us the floor to share updates with #genetics community, delivered by our colleague @mariacerezo.bsky.social

#OpenAccess #gwas #gwasdatahero

Stronger together @ebi.embl.org @NIH

NEWS! Check our wrap-up about #ashg24 https://shorturl.at/WcTiz

Something is missing? Let us know!

🙌 Thanks, ASHG, for giving us the floor to share updates with #genetics community, delivered by our colleague @mariacerezo.bsky.social

#OpenAccess #gwas #gwasdatahero

Stronger together @ebi.embl.org @NIH

#ASHG24 There were two more talks in that session, but I hit my limit for the day. My flight hopefully leaves early tomorrow. That should be a wrap for me this year. See you next year for #ASHG25.

#ASHG24 There were two more talks in that session, but I hit my limit for the day. My flight hopefully leaves early tomorrow. That should be a wrap for me this year. See you next year for #ASHG25.

#ASHG24 There were two more talks in that session, but I hit my limit for the day. My flight hopefully leaves early tomorrow. That should be a wrap for me this year. See you next year for #ASHG25.

#ASHG24 There were two more talks in that session, but I hit my limit for the day. My flight hopefully leaves early tomorrow. That should be a wrap for me this year. See you next year for #ASHG25.

#ASHG24 AU: Resolved so far: 3q29 deletion, 16p11 duplication, 16p11 deletion, 1q21 duplciation, etc.

Example of 16p11 duplication. Again break points are on transposons.

#ASHG24 AU: Resolved so far: 3q29 deletion, 16p11 duplication, 16p11 deletion, 1q21 duplciation, etc.

Example of 16p11 duplication. Again break points are on transposons.

#ASHG24 AU: Resolved so far: 3q29 deletion, 16p11 duplication, 16p11 deletion, 1q21 duplciation, etc.

Example of 16p11 duplication. Again break points are on transposons.

#ASHG24 AU: Resolved so far: 3q29 deletion, 16p11 duplication, 16p11 deletion, 1q21 duplciation, etc.

Example of 16p11 duplication. Again break points are on transposons.

#ASHG24 AU: Ignore the reference and assemble the duplication haplotypes directly.

Different 22q11.2 patients have different deletion-flanking regions.

CTLR-Seq assemblies let you find break points. Guided by pan-genome assembly.*breakpoints localize to transposon sequences.*

#ASHG24 AU: Ignore the reference and assemble the duplication haplotypes directly.

Different 22q11.2 patients have different deletion-flanking regions.

CTLR-Seq assemblies let you find break points. Guided by pan-genome assembly.*breakpoints localize to transposon sequences.*

#ASHG24 AU: Ignore the reference and assemble the duplication haplotypes directly.

Different 22q11.2 patients have different deletion-flanking regions.

CTLR-Seq assemblies let you find break points. Guided by pan-genome assembly.*breakpoints localize to transposon sequences.*

#ASHG24 AU: Ignore the reference and assemble the duplication haplotypes directly.

Different 22q11.2 patients have different deletion-flanking regions.

CTLR-Seq assemblies let you find break points. Guided by pan-genome assembly.*breakpoints localize to transposon sequences.*

#ASHG24 AU: Segmental duplications create loci of genomic instability. Standard reference isn't useful in many of these regions [ unresolved. ]

Can't read through with short reads. or linked reads. or long reads. problematic region.

CRISPR-Catch method. in vitro cutting outside of segmental duplications. remove rest of genome from the region. Then long-read of up to 2Mbp fragment. Resolves segmental duplications and find break points.

#ASHG24 AU: Segmental duplications create loci of genomic instability. Standard reference isn't useful in many of these regions [ unresolved. ]

Can't read through with short reads. or linked reads. or long reads. problematic region.

CRISPR-Catch method. in vitro cutting outside of segmental duplications. remove rest of genome from the region. Then long-read of up to 2Mbp fragment. Resolves segmental duplications and find break points.

#ASHG24 AU: Segmental duplications create loci of genomic instability. Standard reference isn't useful in many of these regions [ unresolved. ]

Can't read through with short reads. or linked reads. or long reads. problematic region.

CRISPR-Catch method. in vitro cutting outside of segmental duplications. remove rest of genome from the region. Then long-read of up to 2Mbp fragment. Resolves segmental duplications and find break points.

#ASHG24 AU: Segmental duplications create loci of genomic instability. Standard reference isn't useful in many of these regions [ unresolved. ]

Can't read through with short reads. or linked reads. or long reads. problematic region.

CRISPR-Catch method. in vitro cutting outside of segmental duplications. remove rest of genome from the region. Then long-read of up to 2Mbp fragment. Resolves segmental duplications and find break points.

#ASHG24 AU: large neuropsychiatric dx associated cnvs share characteristics.

Large. Can be complex with unknown break points.

Example 22q11. 3Mbp. ~50 genes affected. Up to 0.1% of live births. Pleiotropic with high risk of SCZ.

#ASHG24 AU: large neuropsychiatric dx associated cnvs share characteristics.

Large. Can be complex with unknown break points.

Example 22q11. 3Mbp. ~50 genes affected. Up to 0.1% of live births. Pleiotropic with high risk of SCZ.

#ASHG24 AU: large neuropsychiatric dx associated cnvs share characteristics.

Large. Can be complex with unknown break points.

Example 22q11. 3Mbp. ~50 genes affected. Up to 0.1% of live births. Pleiotropic with high risk of SCZ.

#ASHG24 AU: large neuropsychiatric dx associated cnvs share characteristics.

Large. Can be complex with unknown break points.

Example 22q11. 3Mbp. ~50 genes affected. Up to 0.1% of live births. Pleiotropic with high risk of SCZ.

#ASHG24 AU: Alexander Urban. Revealing the exact breakpoints and sequence rearrangements of recurrent, large neuropsychiatric copy number variations (CNVs) at single base-pair resolution using CRISPR-targeted ultra-long read sequencing (CTLR-Seq).

psychiatric disorders have a strong eentic component. GWAS yielded about 300 loci for schizophrenia (SCZ).

[ nice plot showing MAF versus effect size. GWAS hits low effect, but very rare with large effects. ]

#ASHG24 AU: Alexander Urban. Revealing the exact breakpoints and sequence rearrangements of recurrent, large neuropsychiatric copy number variations (CNVs) at single base-pair resolution using CRISPR-targeted ultra-long read sequencing (CTLR-Seq).

psychiatric disorders have a strong eentic component. GWAS yielded about 300 loci for schizophrenia (SCZ).

[ nice plot showing MAF versus effect size. GWAS hits low effect, but very rare with large effects. ]

#ASHG24 AU: Alexander Urban. Revealing the exact breakpoints and sequence rearrangements of recurrent, large neuropsychiatric copy number variations (CNVs) at single base-pair resolution using CRISPR-targeted ultra-long read sequencing (CTLR-Seq).

psychiatric disorders have a strong eentic component. GWAS yielded about 300 loci for schizophrenia (SCZ).

[ nice plot showing MAF versus effect size. GWAS hits low effect, but very rare with large effects. ]

#ASHG24 AU: Alexander Urban. Revealing the exact breakpoints and sequence rearrangements of recurrent, large neuropsychiatric copy number variations (CNVs) at single base-pair resolution using CRISPR-targeted ultra-long read sequencing (CTLR-Seq).

psychiatric disorders have a strong eentic component. GWAS yielded about 300 loci for schizophrenia (SCZ).

[ nice plot showing MAF versus effect size. GWAS hits low effect, but very rare with large effects. ]

#ASHG24 ZT: Incorporate new mutations leads to tracking more recent ancestry.

Several signals across ancient groups. Excess recent ancestry between ancient and modern samples: TCHH, LCT, MCM5, CCR5, TLR1/6, MHC, etc.

#ASHG24 ZT: Incorporate new mutations leads to tracking more recent ancestry.

Several signals across ancient groups. Excess recent ancestry between ancient and modern samples: TCHH, LCT, MCM5, CCR5, TLR1/6, MHC, etc.

#ASHG24 ZT: Incorporate new mutations leads to tracking more recent ancestry.

Several signals across ancient groups. Excess recent ancestry between ancient and modern samples: TCHH, LCT, MCM5, CCR5, TLR1/6, MHC, etc.

#ASHG24 ZT: Incorporate new mutations leads to tracking more recent ancestry.

Several signals across ancient groups. Excess recent ancestry between ancient and modern samples: TCHH, LCT, MCM5, CCR5, TLR1/6, MHC, etc.

#ASHG24 ZT: Focused on West Eurasian ancient genomes. Vikings. Romans. Etc.

Looked at Saxon migrations. Irish Medieval closest to modern Scots.

Look at group migration patterns. Zoom in on area of UK with lots of nordic place names. People there close to viking ancient DNA genomes.

#ASHG24 ZT: Focused on West Eurasian ancient genomes. Vikings. Romans. Etc.

Looked at Saxon migrations. Irish Medieval closest to modern Scots.

Look at group migration patterns. Zoom in on area of UK with lots of nordic place names. People there close to viking ancient DNA genomes.

#ASHG24 ZT: Focused on West Eurasian ancient genomes. Vikings. Romans. Etc.

Looked at Saxon migrations. Irish Medieval closest to modern Scots.

Look at group migration patterns. Zoom in on area of UK with lots of nordic place names. People there close to viking ancient DNA genomes.

#ASHG24 ZT: Focused on West Eurasian ancient genomes. Vikings. Romans. Etc.

Looked at Saxon migrations. Irish Medieval closest to modern Scots.

Look at group migration patterns. Zoom in on area of UK with lots of nordic place names. People there close to viking ancient DNA genomes.

#ASHG24 ZT: TheaDNA is computationally eficient. Linear for ancient samples. Sublinear for the modern walkthroughs.

Simulations to access accuracy. For segments over one cM almost always in right region of closet relative set.

Applied to ARGs for 487k from UKBB and 4800 ancient DNA samples.

Get pairwise measure of sharing between ancient and modern individual over a user set timespan.

#ASHG24 ZT: TheaDNA is computationally eficient. Linear for ancient samples. Sublinear for the modern walkthroughs.

Simulations to access accuracy. For segments over one cM almost always in right region of closet relative set.

Applied to ARGs for 487k from UKBB and 4800 ancient DNA samples.

Get pairwise measure of sharing between ancient and modern individual over a user set timespan.

#ASHG24 ZT: TheaDNA is computationally eficient. Linear for ancient samples. Sublinear for the modern walkthroughs.

Simulations to access accuracy. For segments over one cM almost always in right region of closet relative set.

Applied to ARGs for 487k from UKBB and 4800 ancient DNA samples.

Get pairwise measure of sharing between ancient and modern individual over a user set timespan.

#ASHG24 ZT: TheaDNA is computationally eficient. Linear for ancient samples. Sublinear for the modern walkthroughs.

Simulations to access accuracy. For segments over one cM almost always in right region of closet relative set.

Applied to ARGs for 487k from UKBB and 4800 ancient DNA samples.

Get pairwise measure of sharing between ancient and modern individual over a user set timespan.

#ASHG24 ZT: ThreaDNA method.

Input unphased ancient DNA. Trace two paths through phased modern panel. Output is amalgamation of those segments, i.e. a potential ancient DNA haplotype determined from most likely path through modern genome.

Infer age of segment. Estimate the age given the length. Longer segments should be younger.

#ASHG24 ZT: ThreaDNA method.

Input unphased ancient DNA. Trace two paths through phased modern panel. Output is amalgamation of those segments, i.e. a potential ancient DNA haplotype determined from most likely path through modern genome.

Infer age of segment. Estimate the age given the length. Longer segments should be younger.

#ASHG24 ZT: ThreaDNA method.

Input unphased ancient DNA. Trace two paths through phased modern panel. Output is amalgamation of those segments, i.e. a potential ancient DNA haplotype determined from most likely path through modern genome.

Infer age of segment. Estimate the age given the length. Longer segments should be younger.

#ASHG24 ZT: ThreaDNA method.

Input unphased ancient DNA. Trace two paths through phased modern panel. Output is amalgamation of those segments, i.e. a potential ancient DNA haplotype determined from most likely path through modern genome.

Infer age of segment. Estimate the age given the length. Longer segments should be younger.

#ASHG24 ZT: Ancestral Recombination Graph (ARG) are complex to calculate. Can use them to infer evolutionary history.

Existing methods are difficult to scale. Require high coverage genomes (not available for most ancient genomes). Require phasing (unreliable for ancient genomes).

New method called ThreaDNA.

#ASHG24 ZT: Ancestral Recombination Graph (ARG) are complex to calculate. Can use them to infer evolutionary history.

Existing methods are difficult to scale. Require high coverage genomes (not available for most ancient genomes). Require phasing (unreliable for ancient genomes).

New method called ThreaDNA.

#ASHG24 ZT: Ancestral Recombination Graph (ARG) are complex to calculate. Can use them to infer evolutionary history.

Existing methods are difficult to scale. Require high coverage genomes (not available for most ancient genomes). Require phasing (unreliable for ancient genomes).

New method called ThreaDNA.

#ASHG24 ZT: Ancestral Recombination Graph (ARG) are complex to calculate. Can use them to infer evolutionary history.

Existing methods are difficult to scale. Require high coverage genomes (not available for most ancient genomes). Require phasing (unreliable for ancient genomes).

New method called ThreaDNA.

#ASHG24 ZT: Zoi Tsangalidou. Inference of genome-wide genealogical relationships between ancient and modern individuals.

Genealogical relationship over time can be a tree. Two individuals at a locus eventually coalesce at a common ancestor.

How do you do it genome-wide?

Sequence of trees across the genome. Make an ancestral combination draft. Compact representation of genealogical history. Can incorporate mutation information.

#ASHG24 ZT: Zoi Tsangalidou. Inference of genome-wide genealogical relationships between ancient and modern individuals.

Genealogical relationship over time can be a tree. Two individuals at a locus eventually coalesce at a common ancestor.

How do you do it genome-wide?

Sequence of trees across the genome. Make an ancestral combination draft. Compact representation of genealogical history. Can incorporate mutation information.

#ASHG24 ZT: Zoi Tsangalidou. Inference of genome-wide genealogical relationships between ancient and modern individuals.

Genealogical relationship over time can be a tree. Two individuals at a locus eventually coalesce at a common ancestor.

How do you do it genome-wide?

Sequence of trees across the genome. Make an ancestral combination draft. Compact representation of genealogical history. Can incorporate mutation information.