Inside Genebench-Pro
Case studies
These 10 case studies showcase representative questions from GeneBench-Pro. Each case study includes the original prompt, datasets, and supporting materials. For an overview of the benchmark and key findings, see the announcement blog.
Note: File previews show excerpts from the full datasets.
Case study 1
Somatic oncology: Structural variant-guided tumor therapy benefit-risk decision
Estimate whether a synthetic TXR1-directed inhibitor has positive clinical utility in tumors whose target activation is driven by a structural variant. TXR1, TXR1i, DLR1, and star-allele labels are synthetic benchmark labels.
The target subgroup has to be recovered from long-read, expression, tumor-quality, and pharmacogenomic evidence before benefit and toxicity can be interpreted as a treatment decision.
Files provided to the model
patient_id
analysis_set
age
sex
site
calendar_period
ecog
tumor_burden
prior_lines
prior_resistance
lineage_class
therapy_class
assessed16
benefit16
tox_stop_8wk
time_zero_day
MTB0001
1
73.8
M
S1
P2
2
0.787
3
1
A
TXR1i
0
1
0
MTB0002
1
55.2
M
S3
P1
1
2.637
0
1
A
TXR1i
1
0
0
0
MTB0003
1
68.8
F
S4
P2
0
0.891
2
1
A
TXR1i
1
1
1
0
MTB0004
1
82.8
F
S2
P2
2
4.101
0
0
B
TXR1i
1
0
0
0
MTB0005
1
65.5
F
S1
P3
1
7.0
1
1
A
TXR1i
1
0
0
0
Registry covariates, therapy, week-16 assessment, benefit, and early toxicity.
Case study 2
Functional genomics: CRISPR target validation: lncRNA transcript or genomic locus?
Decide whether an apparent lncRNA dependency is transcript-specific or driven by nearby-locus and neighbor-gene effects.
Transcript-directed evidence has to survive controls for local DNA-locus perturbation, neighbor-gene repression, guide swaps, GC toxicity, and plate effects.
Files provided to the model
guide_id
nominal_target
chr
coord
strand
dist_lnc_tss_bp
dist_neighbor_tss_bp
guide_gc_frac
g001
LINC473
chr7
100014
14
30
0.624
g002
LINC473
chr7
100035
43
67
0.584
g003
LINC473
chr7
100051
116
56
0.622
g004
LINC473
chr7
100066
59
66
0.617
g005
LINC473
chr7
100088
74
77
0.715
Guide coordinates, targets, distances, and GC features.
Case study 3
Statistical genetics: Prioritizing protein drug targets in a linked genetic locus
Estimate direct disease effects for two nearby proteins using cis multivariable Mendelian randomization (cis-MVMR) while handling assay scale, allele orientation, winner's curse, LD, and residual local pleiotropy.
The two proteins share a correlated locus. The analysis has to move from marginal associations to conditional, LD-aware disease effects on a common protein scale.
Files provided to the model
snp
pos_bp
effect_allele
other_allele
maf
beta
se
pval
rs200000
50000000
A
C
0.42215
0.006438668310706808
0.003267330091203412
0.04876727714241972
rs200001
50010126
A
C
0.05709
0.011008993337581301
0.006955239208750407
0.11345916603941006
rs200002
50020253
G
T
0.09021
0.009922014757116319
0.005633023027015518
0.07817048492026045
rs200003
50030379
G
T
0.48399
0.010569215614164573
0.0032291419740237445
0.0010638520681901973
rs200004
50040506
A
G
0.37703
0.007036551378238654
0.0033297592321269802
0.034580976884336506
Screening-stage protein association summaries for PROTA.
Case study 4
Clinical genomics / carrier screening: DRX1 carrier-screening residual risk under CNV and pseudogene calibration
Estimate ancestry-specific carrier frequencies, residual risk after a negative screen, partner carrier frequency, and affected-conceptus risk from carrier-screening assay data.
The residual-risk estimate depends on pseudogene-aware carrier calls, founder-haplotype collapse, ancestry-specific assay calibration, and standardization from tested partners back to the full partner roster.
Files provided to the model
sample_id
collection
ancestry
family_history_tier
S_EUR_0001
screening
EUR
0
S_EUR_0002
screening
EUR
0
S_EUR_0003
screening
EUR
0
S_EUR_0004
screening
EUR
0
S_EUR_0005
screening
EUR
1
Screening-roster adults with ancestry and screening context.
Case study 5
Single-cell genomics: Activated-monocyte eQTL after ambient RNA correction
Estimate a genotype effect on activated-monocyte expression after removing ambient RNA and technical contamination from single-cell RNA-seq data.
Ambient RNA affects both target expression and the marker panel used to call activation state, so correction has to occur before the eQTL model.
Files provided to the model
cell_id
donor
total_umi
HBB
IFI6
ISG15
LST1
CXCL10
D01_C001
D01
1113
7
3
4
83
5
D01_C002
D01
1103
6
3
3
112
10
D01_C003
D01
1141
9
8
12
63
9
D01_C004
D01
1250
7
60
43
2
17
D01_C005
D01
1045
9
1
2
51
15
Per-cell UMI counts for marker genes, contamination markers, and the target gene.
Case study 6
Structural genetics: Nested structural variant: expression support and clinical association
Estimate whether a nested structural subhaplotype inside an anonymous inversion-like locus has a calibrated clinical association and credible expression support.
A nested copy-dosage signal can be confounded by the broader inversion orientation, so dosage calibration, expression support, and clinical modeling have to remain distinct.
Files provided to the model
sample_id
case
age
age_band
sex
pc1
pc2
pc3
ancestry_group
clinic_stratum
recruitment_stream
Q00012
1
50.45
50_64
0
-1.01514
-0.21032
-0.08849
EUR
tertiary
clinic
Q00028
0
57.39
50_64
0
-1.25987
-0.12498
0.2344
EUR
regional
registry
Q00029
1
68.4
65_plus
0
0.91598
0.62177
0.01891
AFR
tertiary
clinic
Q00030
1
74.07
65_plus
1
0.21125
-0.59634
-0.08197
EAS
community
registry
Q00032
1
82.82
65_plus
0
-1.12034
-0.24372
0.14665
EUR
community
clinic
Clinical and covariate data for the full cohort.
Case study 7
Regulatory genomics: Measuring chromatin loop strength after structural-variant and mapping artifact masking
Quantify a focal case-control Hi-C loop-strength difference after removing low-mappability and structural-variant artifacts from the expected-contact background.
The target loop is defined at 20 kb resolution, but the expected-contact model is distorted unless low-mappability contacts and a case-only SV stripe are masked first.
Files provided to the model
bin_id
chrom
start
end
gc_content
mappability
re_sites
0
chr8
400000
420000
0.46199033821572594
0.9787574214704273
5
1
chr8
420000
440000
0.5044124208534677
0.8901084943498397
5
2
chr8
440000
460000
0.43218451584938194
0.9056879289326712
3
3
chr8
460000
480000
0.4733197282681218
0.9376529840664789
3
4
chr8
480000
500000
0.4444956062150748
0.8682565517981877
4
Target-resolution bin annotations.
Case study 8
Statistical genetics: Multi-parent QTL mapping with founder reconstruction
Map a chromosome-1 quantitative-trait locus in an eight-founder recombinant population by reconstructing founder ancestry before testing the phenotype association.
The visible marker data are biallelic, but the biological signal is founder ancestry. A defensible analysis therefore has to reconstruct founder state, check marker orientation, and separate the QTL from a batch-aligned nuisance peak.
Files provided to the model
marker_id
chr
pos_cM
m2_065
2
59.762431265596575
m2_103
2
94.52656615104739
m2_107
2
98.18761427503033
m2_079
2
72.20130244108847
m1_054
1
49.907510212292195
Marker identifiers, chromosomes, and genetic-map positions.
Case study 9
Population genetics: Parent-specific ancestry and recent admixture timing
Infer parent-specific ancestry proportions and recent admixture timing from phased local-ancestry tracts after repairing reciprocal artifacts and a chromosome-specific label inversion.
Ancestry fractions and pulse times both change if reciprocal tract artifacts, chromosome-local label inversion, or map denominators are handled incorrectly.
Files provided to the model
chrom
hap
start_morgan
end_morgan
anc
posterior
low_complexity_frac
chr1
h1
0.03
0.505
A
0.985
0.08
chr1
h1
0.505
0.535
B
0.62
0.92
chr1
h1
0.535
1.478849
A
0.985
0.08
chr1
h1
1.503727
1.852681
B
0.985
0.08
chr1
h1
1.852681
2.422373
A
0.985
0.08
Phased local-ancestry tracts with coordinates, ancestry labels, posterior values, and QC annotations.
Case study 10
Population genetics: Estimating selection from noisy ancient-DNA time series
Infer which of two haploid loci is under stronger positive selection from ancient allele-frequency time series while accounting for allele orientation, directional error, drift, and changing population size.
Noisy ancient trajectories are not directly comparable until both loci are placed on the same derived-allele scale and the provided sample-level sequencing-error values are modeled directly.
Files provided to the model
generation
alt_reads
total_reads
seq_error
sample_year
6
36
40
0.16
-4500
12
34
45
0.16
-4278
18
41
55
0.16
-4056
24
38
70
0.16
-3833
30
36
90
0.16
-3611
Read-count time series for locus A.
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