Evidence map›Paper›PMID 41321990›Full record

ArticleComputational and structural biotechnology journal2025

macpie: Scalable workflow for high-throughput transcriptomic profiling.

Nenad Bartonicek, Xin Liu, Laura Twomey, Michelle Meier, Richard Lupat, Stuart Craig, David Yoannidis, Jason Li, Tim Semple, Kaylene J Simpson and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Computational and structural biotechnology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Nenad BartonicekPeter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia.
Xin LiuPeter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia.
Laura TwomeyPeter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia.
Michelle MeierPeter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia.
Richard LupatPeter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia.
Stuart CraigPeter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia.
David YoannidisPeter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia.
Jason LiPeter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia.
Tim SemplePeter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia.
Kaylene J SimpsonSir Peter MacCallum Department of Oncology, The University of Melbourne, VIC 3010, Australia.
Mark X LiSir Peter MacCallum Department of Oncology, The University of Melbourne, VIC 3010, Australia.
Susanne RammSir Peter MacCallum Department of Oncology, The University of Melbourne, VIC 3010, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-throughput transcriptomic profiling (HTTr) enables scalable characterisation of transcriptional responses to chemical and genetic perturbations. While plate-based technologies such as MAC-Seq, TempO-seq and PLATE-seq have made HTTr more accessible, they pose unique computational challenges for data modelling and integration across modalities. We present Data availability: All code and example datasets used in this study are available in the

Indexed as

Data integrationHigh-throughput transcriptomicsPlate-based screensSoftware

Identifiers

PMID41321990
PMCPMC12664655

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.