Phrases overrepresented in talks

Which words and phrases are over-represented in talk abstracts compared with posters? Each phrase gets an odds ratio: how much more likely an abstract containing it is to be a talk.

Phrases are 1–3-word sequences from the abstract text. Variants of one idea that turn up in mostly the same abstracts (“massively parallel reporter”, “parallel reporter assay”, “MPRA”) are grouped under the best-scoring one, with the rest listed beneath it in small type.

Search for a phrase

The phrases in the figures below (trends, biobanks, what changed in 2026) plus the top 50 each way across all years. See how often talks and posters mention a phrase each year, then which first-author institutions and metro areas write about it (among those with at least one talk mentioning it; an abstract counts for each of its institutions). Hover or focus a row for that institution's own mention rate and odds of a talk. Searching also finds every other phrase in at least 5 talks over all years; for those the counts are exact matches in the abstract text (no titles or plurals), and there is no institution breakdown.

Plot

share of talksshare of posters
Who writes about it Bars

talksposters

Institutions

Metro areas

Year

All years · 2022–2026

15,327 abstracts, 1,544 of them talks: a pooled talk rate of 10.1%. Odds ratios are combined across years (Mantel–Haenszel, stratified by year), so a phrase that rose or fell over time isn't credited with each year's different baseline. 16 abstracts cut off in a booklet are left out of the phrase counts.

Dot plot of the phrases most over-represented in ASHG 2022–2026 talks versus posters, with odds ratios and 95% confidence intervals.
Top 30 phrases each way

More common in talks

PhraseTalksPostersOdds ratio95% CI
human58136421.701.53–1.90
regulatory28715281.951.70–2.25
chromatin1838162.221.87–2.63
loci44226511.731.54–1.95
massively parallel reporteralso parallel reporter, reporter, massively parallel, massively, mpra, parallel reporter assay, reporter assay mpra, assay mpra, reporter assays, parallel reporter assays, reporter assay43874.873.39–7.00
largest1657562.121.78–2.53
enriched27014931.821.58–2.10
chromatin accessibilityalso accessibility883142.762.17–3.51
colocalization1074382.411.94–3.00
elements1376192.171.79–2.63
novel53635331.551.39–1.74
qtlsalso trait loci, quantitative trait loci, quantitative trait, trait, quantitative551613.282.42–4.46
atac-seq722492.752.11–3.58
traits33920711.631.43–1.86
expressionalso gene expression54737141.511.35–1.69
million19610491.821.55–2.14
gwas45029641.521.35–1.71
regulatory elements692592.622.00–3.42
type-specificalso cell type-specific501593.082.25–4.23
gwas loci682512.611.99–3.42
effects45030311.511.34–1.70
enhancer793182.401.87–3.08
disease84663641.451.30–1.61
eqtls903842.261.79–2.86
crispr853452.321.82–2.95
ukalso uk biobank, biobank27916761.621.41–1.86
genes81760931.441.30–1.60
cell types1799841.791.51–2.11
causal26215541.631.41–1.88
non-coding1286271.951.60–2.38

More common in posters

PhraseTalksPostersOdds ratio95% CI
patient12918120.610.50–0.73
case6411210.510.40–0.66
literature266000.410.28–0.60
patients32235760.750.66–0.85
diagnosed467860.530.39–0.71
ngsalso next-generation, next-generation sequencing, sequencing ngs, next-generation sequencing ngs154180.360.22–0.58
family10013560.640.52–0.79
male407120.520.38–0.71
illumina406770.540.40–0.74
quality8011080.650.51–0.81
performed using285320.500.35–0.73
poor194220.450.29–0.69
sangeralso sanger sequencing113140.370.21–0.64
symptoms467060.590.44–0.79
software244490.500.33–0.74
microarrayalso chromosomal microarray153520.430.27–0.70
extracted285030.530.36–0.76
workflow295370.530.37–0.77
evaluation487440.610.46–0.82
regression11814660.720.59–0.88
logisticalso logistic regression335540.560.40–0.79
methods49550880.830.74–0.93
background26028910.790.69–0.91
conclusions11314110.720.59–0.88
presentation234380.510.34–0.77
female598360.650.50–0.85
pcr173580.470.30–0.75
material42070.280.13–0.61
based29230900.810.70–0.92
panel8711170.700.56–0.87

ASHG 2022 · Los Angeles

2,928 abstracts, 349 of them talks: a baseline talk rate of 11.9%.

Dot plot of the phrases most over-represented in ASHG 2022 talks versus posters, with odds ratios and 95% confidence intervals.
The panel at the bottom compares the largest sample size stated in each abstract (e.g. “12,000 individuals”, “N = 500 patients”).

More common in talks

PhraseTalksPostersOdds ratio95% CI
individuals1607871.931.54–2.42
enhancer23444.102.46–6.85
biobankalso uk, uk biobank853542.031.55–2.65
example481612.411.71–3.39
suggesting582192.161.58–2.95
mpraalso parallel reporter, massively parallel reporter, massively, massively parallel, assay mpra, reporter assay mpra1098.373.45–20.27
strikingly1098.373.45–20.27
map26692.961.86–4.70
remain371222.411.64–3.54
gwas loci18393.592.04–6.31
colocalization22553.121.89–5.17
traits823711.831.40–2.40
coronary22563.071.86–5.07
functional904201.791.38–2.33
identified a total869.863.53–27.53
largest371252.351.60–3.44
gwas1085371.711.33–2.18
mouse371282.291.56–3.36
ancestries28852.591.67–4.01
south asian13244.182.13–8.21
loci974741.711.33–2.21
polygenic592491.911.41–2.60
regulatory552271.951.42–2.68
variants associated27832.551.63–3.98
variants21412771.611.28–2.03
profiles351232.251.52–3.32
atherosclerosis10155.122.32–11.29
conducted the largest6219.514.52–84.26
inverse11194.462.13–9.33
underlying human6313.933.78–51.34

More common in posters

PhraseTalksPostersOdds ratio95% CI
normal91930.340.18–0.67
case122220.390.22–0.70
characterized243190.530.35–0.82
male51360.290.12–0.68
syndrome232900.570.37–0.88
patient353910.630.44–0.91
literature61250.370.17–0.82
evaluation51130.350.15–0.82
based656280.710.54–0.95
database121770.500.28–0.90
family273120.620.41–0.93
presence121760.500.28–0.91
diagnosis353770.660.46–0.95
test394100.670.47–0.95
mild3850.290.10–0.86
preliminary61150.400.18–0.90
order81340.450.22–0.91
background454570.690.50–0.96
quality172170.570.35–0.94
ngs51010.390.16–0.93
sangeralso sanger sequencing2710.250.07–0.90
dna464610.700.51–0.97
collected131770.540.31–0.96
characteristics4900.360.14–0.93
main51000.390.17–0.94
rna222560.620.40–0.97
pcr3780.320.11–0.94
years323390.680.46–0.99
proposed71160.460.22–0.98
genotype202340.620.39–0.99

ASHG 2023 · Washington, DC

3,330 abstracts, 341 of them talks: a baseline talk rate of 10.2%.

Dot plot of the phrases most over-represented in ASHG 2023 talks versus posters, with odds ratios and 95% confidence intervals.
The panel at the bottom compares the largest sample size stated in each abstract (e.g. “12,000 individuals”, “N = 500 patients”).

More common in talks

PhraseTalksPostersOdds ratio95% CI
accessibilityalso chromatin accessibility26753.242.05–5.12
effector13235.192.63–10.23
single-cell381472.441.68–3.55
cell typesalso types431772.311.62–3.29
evolutionary19503.522.06–6.01
expansionsalso repeat expansions15334.192.27–7.73
rare variation7226.796.38–112.60
discovered321202.501.67–3.75
disease risk28992.641.71–4.07
currently492232.101.50–2.92
date391632.261.56–3.26
novel associations9136.302.73–14.56
regulatory elements16423.521.97–6.28
constrained11214.802.33–9.92
biobank we identified6316.534.49–60.92
systematically19573.081.82–5.22
chromatin391682.191.52–3.15
neurons291102.461.61–3.75
vivo19583.031.79–5.12
protein abundance787.872.93–21.13
abundance18553.021.76–5.18
noncoding regions8126.072.52–14.62
t2d risk8126.072.52–14.62
ultra-rare9165.152.30–11.53
dose11244.212.07–8.56
repeat25932.501.59–3.93
probabilistic8135.622.37–13.35
apply22782.611.61–4.23
sc-eqtl5313.953.63–53.53
rare variants321372.181.46–3.25

More common in posters

PhraseTalksPostersOdds ratio95% CI
patients758980.660.50–0.86
case142750.440.25–0.75
reported405440.600.43–0.85
showed475990.640.47–0.89
female112120.450.25–0.83
patient324360.610.42–0.89
ngsalso sequencing ngs21060.200.06–0.70
snp142380.510.30–0.88
worldwide61460.380.17–0.83
principal componentsalso principal51300.360.15–0.85
performed using31060.280.10–0.82
conclusions213030.590.38–0.93
adjusted71480.430.20–0.90
male91700.470.24–0.92
include213000.600.38–0.94
factors475590.700.51–0.96
recruited41090.350.14–0.91
developmental delayalso delay, developmental61310.420.19–0.93
regulated1740.170.03–0.87
aim142200.560.32–0.96
diagnosed121970.540.30–0.96
remaining41040.370.14–0.95
described71380.460.22–0.97
polymorphism1670.190.04–0.97
false51130.410.17–0.98
status162350.590.36–0.99
moderate2770.280.08–0.98
biallelic2760.280.08–0.99
illumina101680.530.28–1.00
subjects81450.500.25–1.00

ASHG 2024 · Denver

2,950 abstracts, 339 of them talks: a baseline talk rate of 11.5%.

Dot plot of the phrases most over-represented in ASHG 2024 talks versus posters, with odds ratios and 95% confidence intervals.
The panel at the bottom compares the largest sample size stated in each abstract (e.g. “12,000 individuals”, “N = 500 patients”).

More common in talks

PhraseTalksPostersOdds ratio95% CI
human1416742.051.62–2.58
chromatin accessibilityalso accessibility25474.382.67–7.18
plofalso plof variants12118.633.84–19.38
chromatin431392.601.81–3.73
crispr24543.642.23–5.95
qtlsalso trait loci, quantitative trait loci, quantitative trait, quantitative, trait17304.592.52–8.36
massively parallel reporteralso parallel reporter, massively parallel, massively, reporter, parallel reporter assays, mpra12146.843.18–14.70
neurons341032.741.83–4.10
atac-seq21473.652.16–6.15
fine-mapping24643.071.90–4.96
anthropometricalso anthropometric traits988.803.46–22.37
africans13214.982.50–9.94
diverse773531.891.43–2.49
transcriptomes11165.512.57–11.79
crispri878.903.31–23.93
postmortem12214.602.27–9.32
genetic ancestry groups7510.693.54–32.31
missed19493.151.84–5.39
ancestry groups14293.902.06–7.39
ukalso uk biobank743491.821.37–2.40
traits803891.771.35–2.32
asians13264.032.07–7.85
largest371382.211.51–3.24
regions844151.751.34–2.28
regulatory572511.911.40–2.61
finally461882.041.45–2.87
putative28942.441.58–3.77
cells924711.701.31–2.20
causal variant11204.422.13–9.19
consistent532321.911.39–2.64

More common in posters

PhraseTalksPostersOdds ratio95% CI
patient263530.540.36–0.82
diagnosed81760.350.18–0.71
patients656940.660.50–0.87
diagnosis324010.580.40–0.85
suggested21110.170.05–0.58
clinical838310.700.54–0.90
based606370.670.50–0.90
literature31120.230.08–0.67
software2990.190.05–0.66
array71430.390.18–0.82
accurately61320.360.16–0.81
cases545720.680.50–0.92
exome sequencingalso exome132020.490.28–0.86
illumina61310.370.17–0.81
poor1810.140.03–0.69
genetic factors41070.310.12–0.81
control293470.620.42–0.92
tools152140.530.31–0.91
likely pathogenic61240.390.18–0.86
management81430.440.22–0.89
subjects51110.370.16–0.87
identification172280.570.34–0.93
panel152090.550.32–0.93
microarray1690.160.03–0.82
commonly61170.410.19–0.92
university2730.260.07–0.91
experience3820.320.11–0.94
female101530.510.27–0.96
use414330.700.50–0.98
tumor61110.440.20–0.97

ASHG 2025 · Boston

3,154 abstracts, 263 of them talks: a baseline talk rate of 8.3%. 16 abstracts are cut off mid-text in the booklet itself; they are left out of the phrase counts.

Dot plot of the phrases most over-represented in ASHG 2025 talks versus posters, with odds ratios and 95% confidence intervals.
The panel at the bottom compares the largest sample size stated in each abstract (e.g. “12,000 individuals”, “N = 500 patients”).

More common in talks

PhraseTalksPostersOdds ratio95% CI
loci1015612.882.20–3.77
million512323.002.15–4.19
new764442.461.84–3.27
regulation623682.311.70–3.14
non-coding311333.011.99–4.54
gwas896202.071.57–2.72
largest321442.871.91–4.30
identified N novel8812.044.61–31.44
enhancer21733.642.21–6.00
causal523012.311.66–3.20
hundreds19633.802.25–6.43
cell type-specificalso type-specific15424.472.46–8.12
motifs16494.092.31–7.26
novel1027811.901.46–2.48
implicated392092.431.68–3.50
reporter assay mpraalso assay mpra, parallel reporter, massively parallel reporter, parallel reporter assay, mpra, reporter assay, massively parallel, reporter, massively6417.275.16–57.86
non-coding variants11265.262.60–10.64
causal genes12314.822.47–9.41
regulatory613992.061.51–2.80
cis-regulatory16533.782.14–6.67
genes involved18653.482.04–5.93
revealing241052.901.83–4.59
elements311552.561.70–3.85
risk loci18673.371.98–5.74
driver genes6611.954.00–35.72
expression1048301.811.39–2.35
crispr17633.381.96–5.84
bowel disease ibdalso disease ibd, inflammatory bowel, inflammatory bowel disease, bowel, bowel disease7117.813.08–19.78
pinpointed6710.353.59–29.83
convergent9205.582.56–12.18

More common in posters

PhraseTalksPostersOdds ratio95% CI
patients346720.530.37–0.77
regression123390.400.22–0.71
patient123290.410.23–0.74
pathogenic variantsalso pathogenic62360.300.14–0.67
typically21630.170.05–0.60
improve163650.490.30–0.82
family92560.410.21–0.79
syndrome122920.470.26–0.84
investigated41670.300.12–0.77
sample214110.570.36–0.90
features224200.590.38–0.92
classification51720.360.15–0.84
children21250.220.06–0.79
results10514510.730.57–0.95
literature21230.230.06–0.80
calculated21220.230.07–0.81
autosomal71930.430.21–0.91
initial01200.050.00–0.75
increasing51590.390.16–0.92
group92190.480.25–0.94
overlap51580.390.17–0.92
approach406410.680.48–0.97
management51570.390.17–0.93
age375950.690.48–0.98
variant649350.740.55–0.99
polygenicalso polygenic risk scores, risk scores, polygenic risk183410.600.37–0.98
developmental122560.550.30–0.98
symptoms51510.410.17–0.97
recessivealso autosomal recessive41350.380.15–0.97
logisticalso logistic regression31190.330.11–0.97

ASHG 2026 · Montreal

2,965 abstracts, 252 of them talks: a baseline talk rate of 8.5%.

Dot plot of the phrases most over-represented in ASHG 2026 talks versus posters, with odds ratios and 95% confidence intervals.
The panel at the bottom compares the largest sample size stated in each abstract (e.g. “12,000 individuals”, “N = 500 patients”).

More common in talks

PhraseTalksPostersOdds ratio95% CI
resource341512.671.80–3.96
nearly half7418.395.67–59.62
genetic variation361662.581.76–3.79
regulatory643902.041.50–2.75
disease loci6512.994.14–40.73
h²6512.994.14–40.73
autoimmune diseases8136.952.92–16.57
qtls10225.182.46–10.90
human956831.801.38–2.36
arise12334.162.14–8.07
enriched573541.961.43–2.68
additionally identified5413.383.82–46.82
neanderthal5413.383.82–46.82
antagonistic5413.383.82–46.82
linking271292.431.58–3.75
traits613971.871.38–2.54
rare damaging5510.943.33–35.94
informs5510.943.33–35.94
origins7136.112.48–15.06
opposite9234.472.08–9.60
nearly18742.791.65–4.73
exists7145.692.33–13.87
identified pathogenic569.262.95–29.03
human genetic variation569.262.95–29.03
chromatin states569.262.95–29.03
kinnex569.262.95–29.03
novel765411.741.31–2.31
large563651.851.35–2.53
consequences241162.391.51–3.77
systematic identification578.022.65–24.28

More common in posters

PhraseTalksPostersOdds ratio95% CI
future112790.410.23–0.76
need82280.380.19–0.76
case72070.370.18–0.77
included244290.570.37–0.88
assess122710.470.26–0.84
quality92270.430.22–0.83
study7310050.700.52–0.92
highlights31330.270.09–0.79
normal61740.380.17–0.85
markers21160.220.06–0.78
snps61710.390.18–0.86
support335200.640.44–0.94
used456630.680.49–0.94
principal componentsalso principal21110.230.07–0.82
plasma51530.370.16–0.88
low102230.480.26–0.91
body41370.340.13–0.88
compared436250.690.49–0.97
illumina41300.360.14–0.93
extracted1860.180.04–0.91
population-specific2980.270.08–0.94
investigated61540.440.20–0.97
significantly associated2960.270.08–0.96
platforms1830.190.04–0.95
essential112210.540.29–0.98
suggest203370.620.39–0.99
methods8110440.760.58–1.00
conducted223560.650.41–1.01
conclusion355140.700.48–1.01
review61470.460.21–1.02

Year by year, 2022–2026: the share of talks and of posters mentioning selected phrases. For any other phrase, and who writes about it, look it up above.

For selected phrases, the share of talks and of posters mentioning each one, per year.

Biobanks

How often abstracts mention the most-cited biobanks, 2022–2026, counting common acronyms (UKB, MVP, BBJ). UK Biobank is in about one abstract in eight every year; All of Us grew six-fold. To compare talks with posters for any of them, look it up above.

Share of accepted abstracts mentioning each of eight biobanks per year, with the number of abstracts mentioning it.

What changed in 2026

Clinical vocabulary stopped leaning toward posters. “Patients”, “likely pathogenic” and “diagnosis” leaned toward posters over 2022–2025 (pooled odds ratios 0.6–0.8); in 2026 all three were at least as common in talks. Scanning every phrase for the largest 2026 shifts turns up more of the same: “idiopathic”, “genetic disease” and “therapy”. Click one to look it up.

Suggestive, not established. The top row was chosen before looking at 2026; the bottom row was picked for having the largest shifts, so its p-values overstate the evidence. Across all ~10,800 phrases tested, no single shift survives a false-discovery-rate correction.

Share of talks and of posters mentioning six clinical terms per year, with the odds ratio of a talk before and in 2026 and the p-value for the change.

Sample size

Talks report larger cohorts than posters, every year: the largest human-subject sample size each abstract states (“12,000 individuals”, “N = 450”); the bars span the middle half of abstracts that state one.

Median largest stated sample size per abstract, with interquartile bars, and the share of abstracts stating a sample size, for talks and posters each year.

Words, A to Z

Every word in at least 10 abstracts, in alphabetical order, by the share of abstracts using it. Common English words (“the”, “of”) are left out; forms of one word (“remain”, “remains”) sit side by side and form towers, and the top of each tower is labelled. Hover a point for its word. The year buttons at the top of the page switch years; words keep their place and the scale is the same every year.

Share of all abstracts using each word, words in alphabetical order, 2022–2026 pooled.

Images to download: all years · 2022 · 2023 · 2024 · 2025 · 2026

Words more common in 2026

The same words, now by how strongly each is overrepresented in 2026 abstracts compared with 2022–2025 (one-sided Fisher's exact test per word; higher is stronger). Most of the strongest are general phrasing rather than new topics: “framework” is in 27% of 2026 abstracts against 10% before, and “remains”, “incompletely”, “supporting” and “consistent” rose too. One new topic stands out: “AlphaGenome”, in 31 abstracts, none before. Hover a point for its word; click it to look it up in the table below.

Manhattan-style plot of every word, alphabetically, by minus log10 p for being more common in 2026 abstracts than in earlier years.

−log₁₀ p from a one-sided Fisher's exact test per word; dashed line: Bonferroni correction over every word at 5%. Image to download

Word2026 abstracts 2022–2025 abstractsOdds ratio p

Every word in the figure, the most overrepresented first; scroll the table for more, click a heading to sort. Bold p: significant after Bonferroni correction. A word less common in 2026 has an odds ratio below 1 and p near 1.

Genes

How often each protein-coding gene is named, placed along the genome (hg38). APOE leads every year, with BRCA1, BRCA2 and TP53 next. Gene symbols that in abstracts mostly mean something else (MAF for minor allele frequency, HR for hazard ratio, TF for transcription factor, CAD for coronary artery disease) are left out. Hover a point for its gene; the year buttons at the top of the page switch years.

Manhattan-style plot, one row per year: share of abstracts naming each protein-coding gene, along the genome.

Image to download (every year, one row each)

Score your text

Paste an abstract to count how many of the 196 phrases overrepresented in ASHG talks it uses, and where that count falls among the 15,311 abstracts accepted 2022–2026.

Your text stays on your device. It is scored by this page's own script as you type; nothing is uploaded or saved. Only a rounded percentile is shown, from counts of abstracts per score.

How talks and posters score

share of talksshare of posters

Median talk 13, median poster 9. Hover a score for its counts.

What the score is

The phrases are the 1–3-word phrases more common in talk abstracts than in poster abstracts over 2022–2026, significant after a Bonferroni correction across all 10,816 phrases tested (z ≥ 4.58). Variants of one idea found in mostly the same abstracts (“massively parallel reporter”, “MPRA”) count once. The score is how many of them a text uses, the same way for your text as for every accepted abstract.

Mostly they mark topics (functional genomics, single-cell and chromatin work, very large cohorts) and the way large studies describe their results (“largest”, “novel”, “million”), more than style.

How well it separates talks and posters

To check the score on abstracts it was not built from, the phrase list was rebuilt from 2022–2025 alone (139 phrases) and used to score the 2,965 abstracts of 2026. A random 2026 talk outscores a random 2026 poster 64% of the time (50% would be no better than a coin flip; ties count half). For comparison, ranking abstracts by length alone (how many different words they use) puts the talk ahead 57% of the time, so the phrase count reflects more than talk abstracts running a little longer.

A description, not a verdict. Talks and posters overlap heavily at every score. Accepted abstracts only, and authors can ask for a poster, so this is association, not acceptance odds. Adding phrases to an abstract will raise its score without changing the work.

All 196 phrases

Talks and posters using each phrase in their text, and its odds ratio of a talk, combined across years. Variants listed under a phrase count toward the score too.

PhraseTalksPostersOdds ratio
human58136421.70
regulatory28715281.95
chromatin1838162.22
loci44226511.73
massively parallel reporteralso parallel reporter, reporter, massively parallel, massively, mpra, parallel reporter assay, assay mpra, reporter assay mpra, reporter assays, parallel reporter assays, reporter assay43874.87
largest1657562.12
enriched27014931.82
chromatin accessibilityalso accessibility883142.76
colocalization1074382.41
elements1376192.17
novel53635331.55
qtlsalso trait loci, quantitative trait loci, quantitative trait, trait, quantitative551613.28
atac-seq722492.75
traits33920711.63
expressionalso gene expression54737141.51
million19610491.82
gwas45029641.52
regulatory elements692592.62
type-specificalso cell type-specific501593.08
gwas loci682512.61
effects45030311.51
enhancer793182.40
disease84663641.45
eqtls903842.26
crispr853452.32
ukalso uk biobank, biobank27916761.62
genes81760931.44
cell types1799841.79
causal26215541.63
non-coding1286271.95
single-cell1669211.80
neurons1115292.03
fine-mapping873832.21
fine-mapped471582.96
putative1074912.04
example1608461.79
cell48533621.45
signals20011931.69
discovered1054762.03
variants91771031.42
long-read1316961.88
mapalso maternal and paternal, maps1035042.00
functional38125961.48
causal variants873902.09
cells37625101.47
donors703052.26
resource1296861.82
plofalso plof variants29793.62
meta-analyses521982.56
strikingly27723.75
cis-regulatoryalso cis-regulatory elements552202.46
genomes1769981.67
assays1266761.82
identified89069591.38
nearly823772.08
finally1669111.69
million participants12138.46
novel associations341063.11
eqtl1186141.82
pip25673.74
leveraged753492.11
identified N novel27723.54
ipsc-derived361222.91
fine-map15265.72
conducted the largest13206.66
depleted30903.17
cis622642.22
constraint411562.64
atlas713352.08
hundreds773562.02
genome48634471.38
transcriptomes341142.87
likely causal22593.76
uncovered562492.24
date1428051.67
leveraging1206601.75
bulk975151.84
diseases40928491.39
evolutionary673242.06
including75158781.33
parallel753711.98
replicated944831.84
human cells17384.36
caqtls14285.09
individuals60745381.34
mouse1156281.73
regulation21413921.51
sc-eqtls10157.32
study to date11176.56
validated1629821.59
population-scale391622.51
mechanisms35124891.40
putative target genesalso putative target9108.41
target genes612812.08
single-cell expression quantitative8810.10
clinvar variants14314.82
cassettes7219.33
single-cell expression13285.04
structural variants svsalso svs, variants svs451972.31
mutational622952.04
editing542402.15
constrained431872.36
remain20013621.51
common and rare341242.62
pleiotropic552522.12
cd4 t cells21633.40
spanning864871.83
diverse25216991.45
types we identified9137.07
accessibility profilesalso chromatin accessibility profiles898.75
fertilized7512.18
advances our understanding10196.04
excitatoryalso excitatory neurons391602.41
disease variants17443.87
non-coding variants361382.49
regions32722801.39
human-specific13294.73
multiple transcription6413.27
regulons7610.41
overall26017281.43
hyperexcitability8108.03
loss-of-function1076101.70
glp1r789.14
associations include7710.27
mechanistic774221.85
transcription1519111.57
vivo592842.02
mrna splicing11195.50
effectoralso effector genes361462.45
coding and noncoding12235.04
mice894621.78
human diversity898.13
charcot-marie-tooth disease10156.12
largely1317871.61
enhancers532502.09
variation30521351.39
firing779.27
gwas signals381572.38
striking25852.93
islets11195.37
notably16610981.54
revealing653411.93
pqtl361452.43
heritability1347941.60
variant heritability779.37
burden of somatic6217.23
promoter733711.87
discovery power12294.68
human genomes20603.29
cell-type-specific512492.09
south africa9146.41
splicing1146601.65
4m779.13
methods we implemented6314.30
topologically associating10185.54
identified hundreds23763.00
intervention arm6314.26
framework for dissecting679.68
poison exon778.92
prioritize likely6215.78
neuron-specific10205.46
research participation769.48
kinnex7107.83
selection coefficient8126.72
assemblies361532.37
aso17493.55
rescued22723.04
range of traits6411.77
unprecedented scale8126.83
expression quantitative592811.97
functional genomics281072.64
importantly693491.87
performed the largest13304.32
aldh211234.87
examples include8126.77
tfs291102.59
noncoding552731.99
ancestry populations21663.05
predicted loss10175.33
posterior probability24812.84
identified a total19573.25
biobank we identified10195.23
carriers of rare669.40
helix research688.63
record data12284.41
repressors5215.75
additional gwas5216.60
human brain391682.25
regulatory t cells7107.28
human plasma proteome6411.24
natural selection22722.94
cis-sqtl5120.54
sc-eqtl9195.53
gene regulation613181.91
nhs9175.63
affecting gene8126.44