Genetic diversity and regulatory features of human-specific NOTCH2NL duplications.

Code ↔ Paper

2 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 2 matches

[1] § STAR★Methods › Method details › Predicting TADs associated with NOTCH2NL paralogs using FiberFold ↔ main.py, lines 16 to 55 · score 0.57 · bigWig, FiberFold, CTCF · Report a mismatch
[2] § STAR★Methods › Method details › Visual alignment of NOTCH2NL-CHM13 regions ↔ R/plotAVA.R, lines 1 to 59 · score 0.55 · plotAVA, SVbyEye, insertion, CIGAR, paf, deletion · Report a mismatch

Paper

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The authors' code

Python · 223 lines · 7.4 KB · no license · 1 match

import sys
import torch
import argparse
import numpy as np
import pytorch_lightning as pl
import pytorch_lightning.callbacks as callbacks
import model_simple
from allTrackDataset import GenomeDataset
def main():
args = init_parser()
init_training(args)
def init_parser():
parser = argparse.ArgumentParser(description='FiberFold Training Module.')
# Data and Run Directories
parser.add_argument('--seed', dest='run_seed', default=2806,
type=int,
help='Random seed for training')
parser.add_argument('--save_path', dest='run_save_path', default='checkpoints',
help='Path to the model checkpoint')
# Data directories
parser.add_argument('--datasheet_val', dest='datasheet_val', default='data',
help='datasheet with al data locations', required=True)
parser.add_argument('--datasheet_train', dest='datasheet_train', default='data',
help='datasheet with al data locations', required=True)
parser.add_argument('--mA',dest='ma_bw', default='data',
help='mA bigWig', required=True)
parser.add_argument('--mC',dest='mc_bw', default='data',
help='mC_bigWig', required=True)
parser.add_argument('--hic',dest='hic', default='data',
help='hic dir, npz format', required=True)
parser.add_argument('--ctcf',dest='ctcf', default='data',
help='ctcf chip bw (signal p-value)', required=True)
parser.add_argument('--ctcf_dir',dest='ctcf_dir', default=None,
help='ctcf direction', required=True)
parser.add_argument('--ckpt',dest='ckpt', default=None,
help='ctcf chip bw (signal p-value)', required=False)
parser.add_argument('--n_feat',dest='n_feat', default=3,
help='number of features', required=False)
# Train single stranded or both
args = parser.parse_args(args=None if sys.argv[1:] else ['--help'])
return args
def init_training(args):
# Early_stopping
early_stop_callback = callbacks.EarlyStopping(monitor='val_loss',
min_delta=0.00,
patience=15,
verbose=False,
mode="min")
# Checkpoints
checkpoint_callback = callbacks.ModelCheckpoint(dirpath=f'{args.run_save_path}/models',
save_top_k=10,
monitor='val_loss')
# LR monitor
lr_monitor = callbacks.LearningRateMonitor(logging_interval='epoch')
# Logger
csv_logger = pl.loggers.CSVLogger(save_dir = f'{args.run_save_path}/csv')
all_loggers = csv_logger
# Assign seed
pl.seed_everything(args.run_seed, workers=True)
pl_module = TrainModule(args)
pl_trainer = pl.Trainer(accelerator='gpu',strategy='ddp',
gradient_clip_val=1,
logger = all_loggers,
callbacks = [early_stop_callback,
checkpoint_callback,
lr_monitor],
max_epochs = 120) #fast_dev_run=True) # fast_dev_run to see if model will initialize, remove when running entire model
trainloader = pl_module.get_dataloader(args, 'train')
valloader = pl_module.get_dataloader(args, 'val')
pl_trainer.fit(pl_module, trainloader, valloader, ckpt_path = args.ckpt)
class TrainModule(pl.LightningModule):
def __init__(self, args):
super().__init__()
self.model = self.get_model(args)
self.args = args
self.save_hyperparameters()
def forward(self, x):
return self.model(x)
def proc_batch(self, batch):
features, mat, chrom_info = batch
return features, mat
def training_step(self, batch, batch_idx):
inputs, mat = self.proc_batch(batch)
outputs = self(inputs)
criterion = torch.nn.MSELoss()
loss = criterion(outputs, mat)
metrics = {'train_step_loss': loss}
self.log_dict(metrics, batch_size = inputs.shape[0], prog_bar=True)
return loss
def validation_step(self, batch, batch_idx):
ret_metrics = self._shared_eval_step(batch, batch_idx)
return ret_metrics
def test_step(self, batch, batch_idx):
ret_metrics = self._shared_eval_step(batch, batch_idx)
return ret_metrics
def _shared_eval_step(self, batch, batch_idx):
#original eval step
inputs, mat = self.proc_batch(batch)
outputs = self(inputs)
criterion = torch.nn.MSELoss()
#criterion = torch.nn.PoissonNLLLoss()
loss = criterion(outputs, mat)
return loss
# Collect epoch statistics
def training_epoch_end(self, step_outputs):
step_outputs = [out['loss'] for out in step_outputs]
ret_metrics = self._shared_epoch_end(step_outputs)
metrics = {'train_loss' : ret_metrics['loss']
}
self.log_dict(metrics, prog_bar=True)
def validation_epoch_end(self, step_outputs):
ret_metrics = self._shared_epoch_end(step_outputs)
metrics = {'val_loss' : ret_metrics['loss']
}
self.log_dict(metrics, prog_bar=True)
def _shared_epoch_end(self, step_outputs):
loss = torch.tensor(step_outputs).mean()
return {'loss' : loss}
def configure_optimizers(self):
optimizer = torch.optim.Adam(self.parameters(),
lr = 4e-4,
weight_decay = 0)
import pl_bolts
scheduler = pl_bolts.optimizers.lr_scheduler.LinearWarmupCosineAnnealingLR(optimizer,
warmup_epochs=10, max_epochs=40)
scheduler_config = {
'scheduler': scheduler,
'interval': 'epoch',
'frequency': 1,
'monitor': 'val_loss',
'strict': True,
'name': 'WarmupCosineAnnealing',
}
return {'optimizer' : optimizer, 'lr_scheduler' : scheduler_config}
def get_dataset(self, args, mode):
if mode == 'val':
dataset = GenomeDataset(self.args.datasheet_val, self.args.ma_bw, self.args.mc_bw, self.args.ctcf, self.args.ctcf_dir, self.args.hic)
elif mode == "train":
dataset = GenomeDataset(self.args.datasheet_train, self.args.ma_bw, self.args.mc_bw, self.args.ctcf, self.args.ctcf_dir, self.args.hic,shift=True)
return dataset
def get_dataloader(self, args, mode):
dataset = self.get_dataset(args, mode)
if mode == 'train':
shuffle = True
else: # validation and test settings
shuffle = False
#### SET BATCH SIZE
batch_size = 8
num_workers = 8
dataloader = torch.utils.data.DataLoader(
dataset,
shuffle=shuffle,
batch_size=batch_size,
num_workers=num_workers,
pin_memory=True,
prefetch_factor=1,
persistent_workers=True
)
return dataloader
def get_model(self, args):
model_name = 'ConvTransModel'
num_genomic_features = int(args.n_feat)
ModelClass = getattr(model_simple, model_name)
model = ModelClass(num_genomic_features, mid_hidden = 256)
return model
if __name__ == '__main__':
main()

main.py at commit 3a61fc7, no license · at the source

Overview

Authors: Taylor D Real¹, Prajna Hebbar^2,3, DongAhn Yoo¹, Francesca Antonacci⁴, Ivana Pačar^2,3, Danilo Dubocanin⁵, Mark Diekhans³, Gregory J Mikol⁶, Oyeronke G Popoola⁷, Benjamin J Mallory¹, Mitchell R Vollger⁸, Philip C Dishuck¹, Xavi Guitart¹, Allison N Rozanski¹, Katherine M Munson¹, Kendra Hoekzema¹, Jane E Ranchalis⁸, Shane J Neph⁸, Adriana E Sedeño-Cortés⁸, Benedict Paten^2,3, Sofie R Salama^3,9, Andrew B Stergachis^1,8,10, Evan E Eichler^1,10,11

ORCID iDs: Prajna Hebbar, DongAhn Yoo, Evan E Eichler

Institutions: University of Washington (United States); University of California, Santa Cruz (United States); University of Bari Aldo Moro (Italy); Stanford University (United States); University of California, Riverside (United States); University of North Carolina at Chapel Hill (United States); Brotman Baty Institute (United States); Howard Hughes Medical Institute (United States)

Journal: Cell genomics, volume 6, issue 6, article 101194

Dates: received 15 March 2025; accepted 4 March 2026; published online 30 March 2026; in print June 2026

Type: Research article · Language: English

License: CC BY

Identifiers: DOI 10.1016/j.xgen.2026.101194 · PMID 41916274 · PMCID PMC13261667 · OpenAlex W7143294730

Open access: gold, a free copy (OpenAlex)

Status: code verified (how the code is found and verified)

Categories: human (organism), cellular / molecular (subfield)

Methods: Preprocessing, Statistics, Evoked potentials

Keywords: segmental duplication, human evolution, gene duplications, structural variation, NOTCH2, NOTCH2NL

MeSH: Gene Duplication*, Genetic Variation*, Receptor, Notch2*, Animals, Evolution, Molecular, Haplotypes, Hominidae, Humans, Intercellular Signaling Peptides and Proteins, Nerve Tissue Proteins (* major topic)

Topic: Cerebrovascular and genetic disorders (Clinical Neurology, Medicine), according to OpenAlex

Funding: Burroughs Wellcome Fund; NHGRI NIH HHS (R01 HG010169, R01 HG002385, R01 HG014490); National Institutes of Health (R01HG010169, 1U01HG013744, R01MH120295, 1DP5OD029630, R01HG002385); Howard Hughes Medical Institute; NIMH NIH HHS (R01 MH120295)

Citations: cited by 6 papers (Europe PMC); 77 references in the paper

Research resources: HA-Tag (C29F4) Rabbit mAb #3724 RRID:AB_1549585, GFP (D5.1) Rabbit mAb #2956 RRID:AB_3713179

Abstract

NOTCH2NL (NOTCH2-N-terminus-like) genes arose from ape-specific chromosome 1 segmental duplications implicated in human brain cortical expansion, including an incomplete NOTCH2 gene. Genetic characterization of these loci and their regulation is complicated because they are embedded in large, nearly identical duplications that predispose to recurrent microdeletion syndromes. Using near-complete long-read assemblies generated from 70 human and 12 ape haploid genomes, we show independent recurrent duplication among apes with protein-coding copies emerging in humans 2.2–3.7 million years ago. We distinguish NOTCH2NL paralogs present in every human haplotype (NOTCH2NLA) from copy-number-variable ones. We also characterize large-scale structural variation, including gene conversion, for 28% of haplotypes, leading to a previously undescribed paralog, NOTCH2tv. Finally, we apply Fiber-seq and long-read transcript sequencing to human dorsal forebrain organoids to characterize the regulatory landscape and find that the most fixed paralogs, NOTCH2 and NOTCH2NLA, harbor the greatest number of paralog-specific elements potentially driving their regulation.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repositories

Its files are read in the Code ↔ Paper reader above, with 2 matches between paragraphs and lines of code.

daewoooo/SVbyEye

License: MIT

State: the link answers, verified on 30 September 2026

Evidence: files inventoried

Commit: 5866e7f198b7827628aa95ea3bfa421986a0bbd8, 13 April 2026

Languages: R (38)

Size: 120 files, 38 scripts

Software Heritage: not archived

Found in: the resources table

Holds: README, license file, environment (DESCRIPTION), tests, continuous integration, documentation, 1 notebook

Not found: CITATION.cff

Tools: tidyverse (19 files), ggplot2 (14 files), data.table (1 file)

Availability: 1 check, the latest on 30 September 2026: the link answers

30 September 2026: the link answers

40 files

R/addAlignments.R, R, 147 lines
R/addAnnotation.R, R, 488 lines
R/addSelfAlignments.R, R, 214 lines
R/breakPafAlignment.R, R, 359 lines
R/cigarUtils.R, R, 223 lines
R/disjoinPafAlignments.R, R, 240 lines
R/filterPaf.R, R, 142 lines
R/flipPaf.R, R, 148 lines
R/geom_arrowhead.R, R, 144 lines
R/geom_miropeats.R, R, 102 lines
R/geom_roundrect.R, R, 143 lines
R/geom_wide_arc.R, R, 131 lines
R/getSequenceContent.R, R, 237 lines
R/global.R, R, 14 lines
R/helpers.R, R, 355 lines
R/liftRangesToAlignment.R, R, 228 lines
R/maskFasta.R, R, 71 lines
R/nucmerToPaf.R, R, 43 lines
R/pafAlignmentToBins.R, R, 139 lines
R/pafToCoords.R, R, 186 lines
R/pafToFasta.R, R, 224 lines
R/pafToGaps.R, R, 244 lines
R/plotAVA.R, R, 444 lines, 1 match
R/plotDotp.R, R, 195 lines
R/plotGenome.R, R, 339 lines
R/plotMiro.R, R, 308 lines
R/plotSelf.R, R, 541 lines
R/readPaf.R, R, 126 lines
R/regionsToFasta.R, R, 147 lines
R/subsetPafAlignments.R, R, 361 lines
R/syncRangesDir.R, R, 76 lines
R/timedMessage.R, R, 24 lines
R/utils-pipe.R, R, 12 lines
tests/testthat.R, R, 4 lines
tests/testthat/test_breakPafAlignment.R, R, 21 lines
tests/testthat/test_geomAndPlottingWrappers.R, R, 47 lines
tests/testthat/test_liftRangesToAlignment.R, R, 21 lines
vignettes/SVbyEye.Rmd, R, 696 lines
LICENSE, License, 21 lines
README.md, Text, 41 lines

At the source: github.com/daewoooo/SVbyEye

vpc-ccg/sedef

License: MIT

State: the link answers, verified on 30 September 2026

Evidence: files inventoried

Commit: 5acd139436fe823302f27b7a526299da6db8034f, 28 February 2022

Languages: C/C++ (21), C++ (19), Python (2), Jupyter (1), Shell (1)

Size: 52 files, 44 scripts

Software Heritage: archived

Found in: the resources table

Holds: README, license file, 1 notebook

Not found: CITATION.cff, environment file, tests, continuous integration, documentation

Tools: pandas (2 files), NumPy (1 file), SAMtools (1 file)

Availability: 1 check, the latest on 30 September 2026: the link answers

30 September 2026: the link answers

46 files

extern/argh.h, C/C++, 402 lines
extern/format.cc, C++, 535 lines
extern/format.h, C/C++, 4,028 lines
extern/ksw2.h, C/C++, 178 lines
extern/ksw2_extz2_sse.cc, C++, 299 lines
extern/ostream.h, C/C++, 108 lines
paper/experiments.ipynb, Jupyter, 235 lines
python/sedef.cpp, C++, 131 lines
python/simulations.py, Python, 349 lines
scratch/check-overlap.py, Python, 150 lines
sedef.sh, Shell, 263 lines
src/align.cc, C++, 677 lines
src/align.h, C/C++, 103 lines
src/align_main.cc, C++, 374 lines
src/align_main.h, C/C++, 18 lines
src/chain.cc, C++, 268 lines
src/chain.h, C/C++, 25 lines
src/common.h, C/C++, 99 lines
src/fasta.cc, C++, 142 lines
src/fasta.h, C/C++, 59 lines
src/filter.cc, C++, 110 lines
src/filter.h, C/C++, 25 lines
src/globals.cc, C++, 39 lines
src/globals.h, C/C++, 110 lines
src/hash.cc, C++, 161 lines
src/hash.h, C/C++, 78 lines
src/hit.cc, C++, 216 lines
src/hit.h, C/C++, 55 lines
src/main.cc, C++, 157 lines
src/merge.cc, C++, 109 lines
src/merge.h, C/C++, 23 lines
src/refine.cc, C++, 193 lines
src/refine.h, C/C++, 25 lines
src/search.cc, C++, 471 lines
src/search.h, C/C++, 42 lines
src/search_main.cc, C++, 241 lines
src/search_main.h, C/C++, 25 lines
src/segment.h, C/C++, 58 lines
src/sliding.cc, C++, 168 lines
src/sliding.h, C/C++, 72 lines
src/stats_main.cc, C++, 537 lines
src/stats_main.h, C/C++, 20 lines
src/util.cc, C++, 113 lines
src/util.h, C/C++, 32 lines
LICENSE, License, 21 lines
README.md, Text, 208 lines

At the source: github.com/vpc-ccg/sedef

schneebergerlab/syri

License: MIT

State: the link answers, verified on 30 September 2026

Evidence: files inventoried

Commit: acf72ccf47beffaaeade849fd258827ef24bedf4, 1 July 2026

Languages: Python (11), Shell (2)

Size: 44 files, 13 scripts

Software Heritage: archived

Found in: the resources table

Holds: README, license file, environment (pyproject.toml, setup.py), tests, continuous integration

Not found: CITATION.cff, documentation

Tools: NumPy (4 files), SAMtools (2 files), BEDTools (1 file), pandas (1 file)

Availability: 1 check, the latest on 30 September 2026: the link answers

30 September 2026: the link answers

15 files

example/pipeline.sh, Shell, 55 lines
setup.py, Python, 29 lines
syri/__init__.py, Python, 1 line
syri/pyxFiles/__init__.py, Python, 7 lines
syri/scripts/__init__.py, Python, 1 line
syri/scripts/aligner.py, Python, 4 lines
syri/scripts/chroder.py, Python, 1,019 lines
syri/scripts/chrrev.py, Python, 24 lines
syri/scripts/func.py, Python, 164 lines
syri/scripts/syri.py, Python, 332 lines
syri/scripts/test_validatation.py, Python, 48 lines
test/pytest.py, Python, 64 lines
test/test_data/generate_test_files.sh, Shell, 11 lines
LICENSE, License, 21 lines
README.md, Text, 111 lines

At the source: github.com/schneebergerlab/syri

EichlerLab/pav

License: none: the authors keep all their rights

State: the link answers, verified on 30 September 2026

Evidence: files inventoried

Commit: 88df4dbfa59846b62e2d240b052b069a359ac22e, 23 October 2024

Languages: Python (20), Shell (3)

Size: 56 files, 23 scripts

Software Heritage: not archived

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Holds: README, environment (Dockerfile)

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Tools: NumPy (14 files), pandas (13 files), Biopython (7 files), pysam (5 files), SciPy (2 files), Matplotlib (1 file), Snakemake (1 file)

Availability: 1 check, the latest on 30 September 2026: the link answers

30 September 2026: the link answers

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files/docker/build_deps.sh, Shell, 101 lines
files/docker/build_home.sh, Shell, 20 lines
files/run_scripts/runlocal.sh, Shell, 6 lines
pavlib/__init__.py, Python, 19 lines
pavlib/align/__init__.py, Python, 5 lines
pavlib/align/align.py, Python, 831 lines
pavlib/align/lift.py, Python, 487 lines
pavlib/align/trim.py, Python, 917 lines
pavlib/asmstat.py, Python, 80 lines
pavlib/call.py, Python, 770 lines
pavlib/cigarcall.py, Python, 362 lines
pavlib/constants.py, Python, 55 lines
pavlib/density.py, Python, 361 lines
pavlib/inv.py, Python, 637 lines
pavlib/lgsv.py, Python, 694 lines
pavlib/pipeline.py, Python, 679 lines
pavlib/plot.py, Python, 415 lines
pavlib/seq.py, Python, 360 lines
pavlib/util.py, Python, 122 lines
pavlib/vcf.py, Python, 341 lines
scripts/density.py, Python, 571 lines
scripts/print_version.py, Python, 23 lines
scripts/reconstruct_sam.py, Python, 102 lines
README.md, Text, 190 lines

At the source: github.com/EichlerLab/pav

mrvollger/rustybam

License: MIT

State: the link answers, verified on 30 September 2026

Evidence: files inventoried

Commit: 617f61a4a08b10cbed10af97c74bcc72ad13cd0d, 15 August 2026

Languages: Rust (21), Shell (2)

Size: 87 files, 23 scripts

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30 September 2026: the link answers

25 files

build.rs, Rust, 19 lines
release.sh, Shell, 31 lines
src/add_rg.rs, Rust, 108 lines
src/annotate.rs, Rust, 63 lines
src/bamstats.rs, Rust, 402 lines
src/bed.rs, Rust, 235 lines
src/bed_stats.rs, Rust, 46 lines
src/cli.rs, Rust, 304 lines
src/fastx.rs, Rust, 45 lines
src/getfasta.rs, Rust, 58 lines
src/lib.rs, Rust, 36 lines
src/liftover.rs, Rust, 445 lines
src/main.rs, Rust, 367 lines
src/myio.rs, Rust, 98 lines
src/nucfreq.rs, Rust, 152 lines
src/paf.rs, Rust, 1,735 lines
src/seq_content.rs, Rust, 276 lines
src/seq_stats.rs, Rust, 270 lines
src/suns.rs, Rust, 297 lines
src/trim_overlap.rs, Rust, 186 lines
tests/compare_liftover.sh, Shell, 219 lines
tests/paf_parsing.rs, Rust, 44 lines
tests/visual_tests.rs, Rust, 1,279 lines
LICENSE, License, 21 lines
README.md, Text, 243 lines

At the source: github.com/mrvollger/rustybam

mrvollger/NucFreq

License: MIT

State: the link answers, verified on 30 September 2026

Evidence: files inventoried

Commit: 88ac15a819b2fdbd81806d1a5123e1d8ba03f674, 6 October 2025

Languages: Python (3), R (1), Shell (1)

Size: 9 files, 5 scripts

Software Heritage: not archived

Found in: the resources table

Holds: README, license file

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Tools: pandas (3 files), pysam (3 files), Matplotlib (2 files), NumPy (2 files), seaborn (2 files), Biopython (1 file), data.table (1 file), ggplot2 (1 file), reshape2 (1 file), tidyverse (1 file)

Availability: 1 check, the latest on 30 September 2026: the link answers

30 September 2026: the link answers

7 files

HetDetection.R, R, 105 lines
Mutate.py, Python, 63 lines
NucPlot.py, Python, 473 lines
RM.sh, Shell, 15 lines
TruthBamToMatrix.py, Python, 98 lines
LICENSE, License, 22 lines
README.md, Text, 80 lines

At the source: github.com/mrvollger/NucFreq

KiddLab/fastCN

License: GPL-3.0

State: the link answers, verified on 30 September 2026

Evidence: files inventoried

Commit: 538a5d8dd1b05d2a75535a2bfa2f8c95473bed7a, 11 July 2022

Languages: Python (34), C++ (2), C (2)

Size: 55 files, 38 scripts

Software Heritage: not archived

Found in: the resources table

Holds: README, license file

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Tools: NumPy (8 files), Matplotlib (4 files), SAMtools (2 files)

Availability: 1 check, the latest on 30 September 2026: the link answers

30 September 2026: the link answers

40 files

GC_control_gen.cc, C++, 247 lines
SAM_GC_correction.cc, C++, 297 lines
depth-to-cn.py, Python, 235 lines
depth_combine.c, C, 346 lines
extract-from-bam-36.py, Python, 89 lines
extract-from-fastq36-pair.py, Python, 111 lines
extract-from-fastq36.py, Python, 79 lines
half_float_convert.c, C, 296 lines
lowess.py, Python, 41 lines
make-colortrack-fordisplay.py, Python, 149 lines
masking-info/masking-scripts/bed-length.py, Python, 40 lines
masking-info/masking-scripts/combine-rm.py, Python, 107 lines
masking-info/masking-scripts/combine-trf.py, Python, 71 lines
masking-info/masking-scripts/convert-RM-to-bed.py, Python, 68 lines
masking-info/masking-scripts/convert-dustout-to-bed.py, Python, 41 lines
masking-info/masking-scripts/count-kmer-maps.py, Python, 86 lines
masking-info/masking-scripts/extract-50mers.py, Python, 71 lines
masking-info/masking-scripts/extract-chunks.py, Python, 58 lines
masking-info/masking-scripts/genutils3.py, Python, 270 lines
masking-info/masking-scripts/get-gaps-bed.py, Python, 48 lines
masking-info/masking-scripts/select-50.py, Python, 57 lines
masking-info/masking-scripts/trf-to-bed.py, Python, 43 lines
masking-info/masking-scripts/write-chunk-coords.py, Python, 85 lines
masking-info/masking-scripts/write-mrsfast-ksearch-cmds.py, Python, 52 lines
masking-info/masking-scripts/write-rm.py, Python, 13 lines
masking-info/masking-scripts/write-trf.py, Python, 14 lines
mrsFAST-CNV-main.py, Python, 47 lines
other-scripts/make-colortrack-fordisplay.py, Python, 149 lines
other-scripts/make-equal-windows.py, Python, 100 lines
other-scripts/old-python2-versions/depth-to-cn.py, Python, 231 lines
other-scripts/old-python2-versions/extract-from-bam-36.py, Python, 89 lines
other-scripts/old-python2-versions/extract-from-fastq36-pair.py, Python, 111 lines
other-scripts/old-python2-versions/extract-from-fastq36.py, Python, 79 lines
other-scripts/old-python2-versions/perbp-to-windows.py, Python, 166 lines
other-scripts/old-python2-versions/smooth_GC_mrsfast.py, Python, 77 lines
other-scripts/write-color-key.py, Python, 33 lines
perbp-to-windows.py, Python, 183 lines
smooth_GC_mrsfast.py, Python, 84 lines
LICENSE, License, 674 lines
README.md, Text, 282 lines

At the source: github.com/KiddLab/fastCN

marbl/verkko

License: none: the authors keep all their rights

State: the link answers, verified on 30 September 2026

Evidence: files inventoried

Commit: cb69f969eebfa2b2a74003a120edabf2b084248f, 25 August 2026

Languages: Python (65), Shell (5), Perl (2)

Size: 109 files, 72 scripts

Software Heritage: archived

Found in: the resources table

Holds: README, continuous integration

Not found: license file, CITATION.cff, environment file, tests, documentation

Tools: NetworkX (10 files), pysam (4 files), NumPy (3 files), Biopython (1 file), SAMtools (1 file), Snakemake (1 file)

Availability: 1 check, the latest on 30 September 2026: the link answers

30 September 2026: the link answers

73 files

scripts/buildRelease.sh, Shell, 72 lines
src/profiles/jobscript.sh, Shell, 2 lines
src/profiles/slurm-sge-status.sh, Shell, 160 lines
src/profiles/slurm-sge-submit.sh, Shell, 192 lines
src/scripts/add_fake_alignments.py, Python, 54 lines
src/scripts/add_fake_bridging_paths.py, Python, 38 lines
src/scripts/add_hairpin_uniques.py, Python, 90 lines
src/scripts/add_hom_node_scaffold_edges.py, Python, 145 lines
src/scripts/bam_rename.py, Python, 99 lines
src/scripts/calculate_coverage.py, Python, 60 lines
src/scripts/check_layout_gaps.py, Python, 50 lines
src/scripts/chop_misassemblies.py, Python, 203 lines
src/scripts/circularize_ctgs.py, Python, 82 lines
src/scripts/cluster.py, Python, 685 lines
src/scripts/connect_uniques.py, Python, 143 lines
src/scripts/estimate_unique_local.py, Python, 569 lines
src/scripts/fasta_combine.py, Python, 115 lines
src/scripts/fasta_extract.py, Python, 64 lines
src/scripts/fasta_filter.py, Python, 37 lines
src/scripts/fasta_partition.py, Python, 125 lines
src/scripts/fasta_util.py, Python, 166 lines
src/scripts/filter_alignments_by_column.py, Python, 28 lines
src/scripts/find_bridges.py, Python, 49 lines
src/scripts/find_tips.py, Python, 60 lines
src/scripts/fix_diploid_paths.py, Python, 144 lines
src/scripts/fix_diploid_unique_nodes.py, Python, 162 lines
src/scripts/fix_haplogaps.py, Python, 266 lines
src/scripts/forbid_unbridged_tangles.py, Python, 163 lines
src/scripts/get_bridge_mapping.py, Python, 24 lines
src/scripts/get_layout_from_mbg.py, Python, 733 lines
src/scripts/get_original_coverage.py, Python, 210 lines
src/scripts/get_paths_fasta.py, Python, 17 lines
src/scripts/get_unroll_mapping.py, Python, 25 lines
src/scripts/get_utig1_from_utig4.py, Python, 202 lines
src/scripts/graph_functions.py, Python, 423 lines
src/scripts/hic_prefilter.py, Python, 113 lines
src/scripts/inject_coverage.py, Python, 53 lines
src/scripts/insert_aln_gaps.py, Python, 253 lines
src/scripts/launch_phasing.py, Python, 46 lines
src/scripts/launch_scaffolding.py, Python, 56 lines
src/scripts/logging_utils.py, Python, 73 lines
src/scripts/match_kmers_simple.py, Python, 129 lines
src/scripts/maybe_trim_alignment.py, Python, 67 lines
src/scripts/merge_layouts.py, Python, 126 lines
src/scripts/merge_unresolved_dbg_nodes.py, Python, 182 lines
src/scripts/parse_sam_pairs.py, Python, 52 lines
src/scripts/pick_majority_bridge.py, Python, 51 lines
src/scripts/pop_bubbles_coverage_based.py, Python, 391 lines
src/scripts/prepare_scaffolding.py, Python, 51 lines
src/scripts/remove_contained_spurious_uniques.py, Python, 165 lines
src/scripts/remove_crosslink_paths.py, Python, 121 lines
src/scripts/remove_nodes_add_telomere.py, Python, 165 lines
src/scripts/remove_wrong_connections_2.py, Python, 51 lines
src/scripts/replace_path_nodes.py, Python, 47 lines
src/scripts/resolve_triplets_kmerify.py, Python, 1,097 lines
src/scripts/scaffolding/match_graph.py, Python, 353 lines
src/scripts/scaffolding/path_storage.py, Python, 171 lines
src/scripts/scaffolding/scaff_prefilter.py, Python, 78 lines
src/scripts/scaffolding/scaffold_graph.py, Python, 1,462 lines
src/scripts/screen-assembly.pl, Perl, 649 lines
src/scripts/select_best_alignment.py, Python, 128 lines
src/scripts/select_unused_reads.py, Python, 39 lines
src/scripts/translate_nodes_by_seq.py, Python, 34 lines
src/scripts/translate_uniques.py, Python, 25 lines
src/scripts/trim_dbg_alignment.py, Python, 44 lines
src/scripts/trio_split_by_markers.py, Python, 118 lines
src/scripts/unitigify.py, Python, 130 lines
src/scripts/unroll_simple_loops.py, Python, 126 lines
src/scripts/unroll_tip_loops.py, Python, 167 lines
src/scripts/untip_relative.py, Python, 100 lines
src/scripts/version_update.pl, Perl, 230 lines
src/verkko.sh, Shell, 1,568 lines
README.md, Text, 204 lines

At the source: github.com/marbl/verkko

fiberseq/fiberseq-fire

License: MIT

State: the link answers, verified on 30 September 2026

Evidence: files inventoried

Commit: 6e1c24e2b6fe0d81b2df6abdb1ca8b03b690fbbe, 15 August 2026

Languages: Python (7), Shell (5), R (2)

Size: 100 files, 14 scripts

Software Heritage: not archived

Found in: “Fiber-seq and identification of chromatin access”

Holds: README, license file, environment (pixi.lock, pixi.toml, workflow/envs/env.yaml), tests, continuous integration, documentation

Not found: CITATION.cff

Tools: NumPy (4 files), pandas (4 files), cowplot (2 files), data.table (2 files), ggpubr (2 files), tidyverse (2 files), ggplot2 (1 file), Matplotlib (1 file), patchwork (1 file), pysam (1 file), scikit-learn (1 file), Snakemake (1 file), XGBoost (1 file)

Availability: 1 check, the latest on 30 September 2026: the link answers

30 September 2026: the link answers

16 files

Train-FIRE-v2.0/mixed-positives/download.sh, Shell, 9 lines
Train-FIRE-v2.0/train-fire-model.py, Python, 322 lines
tests/dry-run-checks.sh, Shell, 138 lines
tests/generate-test-bams.py, Python, 69 lines
tests/verify-multi.sh, Shell, 80 lines
tests/verify-results.sh, Shell, 28 lines
workflow/scripts/cov.py, Python, 92 lines
workflow/scripts/fdr-table.py, Python, 338 lines
workflow/scripts/hap-diffs.R, R, 269 lines
workflow/scripts/merge_fire_peaks.py, Python, 191 lines
workflow/scripts/peaks-vs-percent.R, R, 128 lines
workflow/scripts/percent-in-clusters.py, Python, 34 lines
workflow/scripts/percent-in-clusters.sh, Shell, 32 lines
workflow/scripts/trackhub.py, Python, 324 lines
LICENSE, License, 21 lines
README.md, Text, 10 lines

At the source: github.com/fiberseq/fiberseq-fire

altemoselab/fiberFold

License: none: the authors keep all their rights

State: the link answers, verified on 30 September 2026

Evidence: files inventoried

Commit: 3a61fc70d50def64b85657ce93c4b0628582c194, 28 March 2025

Languages: Python (9)

Size: 11 files, 9 scripts

Software Heritage: not archived

Found in: the resources table

Holds: README

Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation

Tools: NumPy (8 files), PyTorch (5 files), BEDTools (2 files), pandas (2 files), PyTorch Lightning (1 file), Matplotlib (1 file), scikit-image (1 file)

Availability: 1 check, the latest on 30 September 2026: the link answers

30 September 2026: the link answers

10 files

allTrackDataset.py, Python, 123 lines
blocks_simple.py, Python, 199 lines
main.py, Python, 223 lines, 1 match
misc/encodeFP.py, Python, 122 lines
misc/encodeMotifDirection.py, Python, 70 lines
misc/filterOverlapMotifs.py, Python, 39 lines
model_simple.py, Python, 73 lines
predict.py, Python, 107 lines
shapeData.py, Python, 171 lines
README.md, Text, 105 lines

At the source: github.com/altemoselab/fiberFold

Materials availability

The DNA sequence of plasmids generated in this study for NOTCH2NL protein expression has been deposited to GitHub: https://github.com/tdreal/NOTCH2NL-0325/tree/main and Zenodo: https://zenodo.org/records/15022214.

Reproduced under the paper's license (CC BY), from the paper cited above.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

10 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
279 scripts, each with its path and the digest of its content;
2 matches between paragraphs of the paper and lines of the code (method lexical-v1);
neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

geo:GSE186009, at NCBI GEO; found in the resources table
github.com/tdreal/notch2nl-0325, at github.com; found in “Data and code availability”
zenodo:15022214, at Zenodo; found in “Data and code availability”

Data and code availability

PacBio HiFi Fiber-seq and Kinnex full-length Iso-Seq from HG02630 brain organoids generated for this study have been made available on NCBI with the BioProject ID: PRJNA1236375. Full-length Iso-Seq from NHAs generated by the Pollen lab for another study that is not yet published are available on NCBI with the BioProject ID: (pending approval). Original western blot images are deposited to GitHub: https://github.com/tdreal/NOTCH2NL-0325/tree/main and Zenodo: https://zenodo.org/records/15022214. No original code is reported in this study. Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 23 authors, 6 keywords, 10 MeSH terms, 5 funders, 77 references, 2 RRIDs.

Cite

This paper

Real, T. D., Hebbar, P., Yoo, D., Antonacci, F., Pačar, I., Dubocanin, D., Diekhans, M., Mikol, G. J., Popoola, O. G., Mallory, B. J., Vollger, M. R., Dishuck, P. C., Guitart, X., Rozanski, A. N., Munson, K. M., Hoekzema, K., Ranchalis, J. E., Neph, S. J., Sedeño-Cortés, A. E., . . . Eichler, E. E. (2026). Genetic diversity and regulatory features of human-specific NOTCH2NL duplications. Cell genomics, 6(6), 101194. https://doi.org/10.1016/j.xgen.2026.101194

BibTeX

@article{real2026genetic, author = {Real, Taylor D and Hebbar, Prajna and Yoo, DongAhn and Antonacci, Francesca and Pačar, Ivana and Dubocanin, Danilo and Diekhans, Mark and Mikol, Gregory J and Popoola, Oyeronke G and Mallory, Benjamin J and Vollger, Mitchell R and Dishuck, Philip C and Guitart, Xavi and Rozanski, Allison N and Munson, Katherine M and Hoekzema, Kendra and Ranchalis, Jane E and Neph, Shane J and Sedeño-Cortés, Adriana E and Paten, Benedict and Salama, Sofie R and Stergachis, Andrew B and Eichler, Evan E}, title = {{Genetic diversity and regulatory features of human-specific NOTCH2NL duplications}}, journal = {Cell genomics}, year = {2026}, month = mar, volume = {6}, number = {6}, pages = {101194}, publisher = {Elsevier}, issn = {2666-979X}, doi = {10.1016/j.xgen.2026.101194}, url = {https://doi.org/10.1016/j.xgen.2026.101194}, pmid = {41916274}, pmcid = {PMC13261667} }

RIS

TY - JOUR AU - Real, Taylor D AU - Hebbar, Prajna AU - Yoo, DongAhn AU - Antonacci, Francesca AU - Pačar, Ivana AU - Dubocanin, Danilo AU - Diekhans, Mark AU - Mikol, Gregory J AU - Popoola, Oyeronke G AU - Mallory, Benjamin J AU - Vollger, Mitchell R AU - Dishuck, Philip C AU - Guitart, Xavi AU - Rozanski, Allison N AU - Munson, Katherine M AU - Hoekzema, Kendra AU - Ranchalis, Jane E AU - Neph, Shane J AU - Sedeño-Cortés, Adriana E AU - Paten, Benedict AU - Salama, Sofie R AU - Stergachis, Andrew B AU - Eichler, Evan E TI - Genetic diversity and regulatory features of human-specific NOTCH2NL duplications T2 - Cell genomics J2 - Cell Genom PY - 2026 DA - 2026/03/30 VL - 6 IS - 6 SP - 101194 SN - 2666-979X PB - Elsevier DO - 10.1016/j.xgen.2026.101194 UR - https://doi.org/10.1016/j.xgen.2026.101194 LA - en ER -

CSL-JSON

{ "id": "10.1016/j.xgen.2026.101194", "type": "article-journal", "title": "Genetic diversity and regulatory features of human-specific NOTCH2NL duplications", "container-title": "Cell genomics", "author": [ { "family": "Real", "given": "Taylor D" }, { "family": "Hebbar", "given": "Prajna" }, { "family": "Yoo", "given": "DongAhn" }, { "family": "Antonacci", "given": "Francesca" }, { "family": "Pačar", "given": "Ivana" }, { "family": "Dubocanin", "given": "Danilo" }, { "family": "Diekhans", "given": "Mark" }, { "family": "Mikol", "given": "Gregory J" }, { "family": "Popoola", "given": "Oyeronke G" }, { "family": "Mallory", "given": "Benjamin J" }, { "family": "Vollger", "given": "Mitchell R" }, { "family": "Dishuck", "given": "Philip C" }, { "family": "Guitart", "given": "Xavi" }, { "family": "Rozanski", "given": "Allison N" }, { "family": "Munson", "given": "Katherine M" }, { "family": "Hoekzema", "given": "Kendra" }, { "family": "Ranchalis", "given": "Jane E" }, { "family": "Neph", "given": "Shane J" }, { "family": "Sedeño-Cortés", "given": "Adriana E" }, { "family": "Paten", "given": "Benedict" }, { "family": "Salama", "given": "Sofie R" }, { "family": "Stergachis", "given": "Andrew B" }, { "family": "Eichler", "given": "Evan E" } ], "container-title-short": "Cell Genom", "volume": "6", "issue": "6", "page": "101194", "DOI": "10.1016/j.xgen.2026.101194", "PMID": "41916274", "PMCID": "PMC13261667", "ISSN": "2666-979X", "publisher": "Elsevier", "URL": "https://doi.org/10.1016/j.xgen.2026.101194", "language": "en", "issued": { "date-parts": [ [ 2026, 3, 30 ] ] } }

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Genetic diversity and regulatory features of human-specific NOTCH2NL duplications.

Code ↔ Paper

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daewoooo/SVbyEye

vpc-ccg/sedef

schneebergerlab/syri

EichlerLab/pav

mrvollger/rustybam

mrvollger/NucFreq

KiddLab/fastCN

marbl/verkko

fiberseq/fiberseq-fire

altemoselab/fiberFold

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