Evidence map›Paper›PMID 38213823›Full record

ArticleBioinformatics advances2024

Quantifying orthogonal barcodes for sequence census assays.

A Sina Booeshaghi, Kyung Hoi Joseph Min, Jase Gehring, Lior Pachter

Abstract read
In one paragraph

Article in Bioinformatics advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Scalable design of orthogonal DNA barcode libraries.Nature computational science · 2024
    Article
  5. Article
  6. Universal preprocessing of single-cell genomics data.bioRxiv : the preprint server for biology · 2023
    Article
  7. Article
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

4 authors.

A Sina BooeshaghiDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, United States.ORCID https://orcid.org/0000-0002-6442-4502
Kyung Hoi Joseph MinDepartment of Computer Science and Electrical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, United States.
Jase GehringArcadia Science, Berkeley, CA 94702, United States.
Lior PachterDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, United States.ORCID https://orcid.org/0000-0002-9164-6231

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Summary: Barcode-based sequence census assays utilize custom or random oligonucloetide sequences to label various biological features, such as cell-surface proteins or CRISPR perturbations. These assays all rely on barcode quantification, a task that is complicated by barcode design and technical noise. We introduce a modular approach to quantifying barcodes that achieves speed and memory improvements over existing tools. We also introduce a set of quality control metrics, and accompanying tool, for validating barcode designs. Availability and implementation: https://github.com/pachterlab/kb_python, https://github.com/pachterlab/qcbc.

Identifiers

PMID38213823
PMCPMC10783946

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.