Systematic discovery of conserved short linear motifs (SLiMs) in intrinsically disordered regions (IDRs) of high-confidence autism risk genes (SFARI Category 1, n=242) versus length-matched controls (n=251 non-SFARI Swiss-Prot human proteins).
1. Data Acquisition - SFARI Gene List + UniProt Swiss-Prot sequences 2. Quality Control - Sequence validation, length distribution, AA composition 3. IDR Prediction - IUPred3 REST API (score > 0.5, min 15 AA) 4. Control Set - Length-matched non-SFARI proteins (±10–50%, seed=42) 5. Motif Discovery - MEME v5.5.9 discriminative mode (case/control) 6. Validation - TOMTOM vs ELM, bootstrap (1000×), shuffled control, spike-in control 7. Enrichment - Fisher's exact test + Benjamini-Hochberg FDR
| Result | Detail |
|---|---|
| Autism IDRs | 1,502 from 217/242 proteins |
| Control IDRs | 1,130 from 196/251 proteins |
| Significant motifs | 3 (poly-H, poly-Q, structured M-S/T-T/S-I/V-M-E-T-T-T-T-M/L-A-T/S) |
| Validated stable | Motif 3 bootstrap 98.6% detection (1000×) |
| TOMTOM best hit | DEG_SPOP_SBC_1 (SPOP-binding degron, p=0.005) |
| Shuffled control | 0 significant motifs (not due to composition noise) |
| Positive control | 4/4 spiked SLiMs recovered (pipeline validates) |
| Enriched (FDR q<0.05) | poly-Q: OR=4.5, q=0.00022; poly-H: OR=∞, q=0.0059 |
- SFARI Gene List: https://gene.sfari.org/human-gene (
00-raw/SFARI-Gene_genes.csv) - UniProt Swiss-Prot:
rest.uniprot.org/uniprotkb/stream(00-raw/uniprot_sprot_human.fasta) - IUPred3:
iupred3.elte.hu/iupred3/{accession}
- Python 3.10+ with: requests, biopython, pandas, numpy, scipy
- MEME Suite v5.5.9: https://meme-suite.org/meme/tools/meme
- TOMTOM: https://meme-suite.org/meme/tools/tomtom
- Control selection: 42
- Shuffle control: 99
- Spike-in control: 7
- Bootstrap: 42
00-raw/ # Raw data: SFARI CSV, UniProt sequences, IUPred3 IDRs
01-control-data/ # Length-matched controls, shuffled controls
02-motif-discovery/ # MEME inputs (positive control spike-in)
03-analysis/ # MEME XML, TOMTOM results, bootstrap, enrichment
04-docs/ # Documentation: index.html, project-steps.md, parameters.log, qc-summary.txt
scripts/ # All analysis scripts (00-*.py through 09-*.py)
Open interactive pipeline report in a browser.
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