GEO series

Evaluation of novel computational methods that identify RNA-binding protein footprints from structural data

GSE262542 Homo sapiens (human) RNA-seq (gene expression) 20 samples Submitted 2025/05/23 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 20 samples

What it is: RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism: Homo sapiens (human)
Samples: 20 samples
Data you can get: A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper: Evaluation of novel computational methods to identify RNA-binding protein footprints from structural dataRNA (New York, N.Y.) · 2025

Summary (written by the submitters)

RNA binding proteins (RBP) play diverse roles in mRNA processing and function. However, from over 1,000 RBPs encoded in the human genome, a detailed molecular understanding of their interactions with RNA is available only for a small fraction. In most cases, our knowledge of the combination of RNA sequence and structure required for specific binding is insufficient for enabling exhaustive prediction of binding sites transcriptome-wide.

Read the full summary ↓

In that context, the rapidly expanding collection of transcriptomic datasets that map distinct, yet intertwined post-transcriptional marks, such as RNA structure and RBP binding, presents an opportunity to integratively analyze them in order to better characterize binding. A grand challenge faced by our community is that relatively little information on the structural context of RNA-protein interactions has been gleaned from integrating such datasets, partially due to lack of suitable methods. To engage scientists from diverse backgrounds in addressing this gap, the RNA Society organized the RBP Footprint Grand Challenge⸺an international community effort to develop new methods or leverage existing ones for predicting RBP binding sites through analysis of a growing volume of sequence, structure, and binding data and to experimentally validate select predictions. Here, we report the initiative, analyses and methods developed by the participants, validation results, and several new in vivo binding datasets generated for validation. We hope this work will inspire additional innovation in computational methods, further utilization of available data resources, and future endeavors to engage the community in collaborating towards closing other critical data analysis gaps.

Published in

Evaluation of novel computational methods to identify RNA-binding protein footprints from structural data

Mizrahi O, Corley M, Feldman O et al. · RNA (New York, N.Y.) 2025 · PMID 40399037 · doi:10.1261/rna.080215.124

This dataset

Open GSE262542 in finder → Find more human RNA-seq datasets →

Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE262542_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1092254 and SRA study SRP497980. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40399037) ↗

Samples in this study

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+ 20 more — browse all 20 samples with per-sample file links →

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