Additional file 7 of Respiratory syncytial virus (RSV) enhances translation of virus-resembling AU-rich host transcripts
Bibliographic record
Abstract
Supplementary Material 7: Supplementary Table S1. RNA-seq raw counts from this study, related to Fig. 2. Columns A-E contain gene information. Columns F-K mock-infected and columns L-Q RSV-infected raw counts. Total indicates total RNA and pol indicates polysome-associated RNA. Supplementary Table S2. DESeq2 normalized counts and DESeq2 differential expression for total RNA from this study, related to Fig. 2B. Columns A-E contain gene information. Columns F-K DESeq2 contain outputs for RSV/mock comparisons for total RNA. Columns L-Q contain normalized total counts. Supplementary Table S3. DESeq2 normalized counts and DESeq2 differential expression for polysome-associated RNA from this study, related to Fig. 2C. Columns A-E contain gene information. Columns F-K DESeq2 contain outputs for RSV/mock comparisons for polysome-associated RNA. Columns L-Q contain normalized polysome-associated counts. Supplementary Table S4. DESeq2 normalized counts and DESeq2 differential expression for translation efficiencies from this study, related to Fig. 2D. Columns A-E contain gene information. Columns F-K DESeq2 outputs for translation efficiency between RSV- and mock- infected cells. Columns L-Q normalized mock-infected counts and columns R-W normalized RSV-infected counts. Columns X-Y shows individual manually calculated TE for mock- and RSV-infected cells. Supplementary Table S5: GO analysis lists of differentially upregulated transcripts. Gene names of significantly upregulated total mRNAs, polysomal mRNAs and TE used for input files for GO analysis. TE: translation efficiency. Supplementary Table S6. DESeq2 differential expression for the translation efficiency data for mock and RSV infected samples from this study, related to Fig. 3. Columns A-D contain gene information. Columns E-I DESeq2 outputs for translation efficiency for mock-infected samples. Columns J-N DESeq2 outputs for translation efficiency for RSV-infected samples. Supplementary Table S7. DESeq2 differential expression for the translation efficiencydata for mock and VSV samples from [34], related to Fig. 4. Columns A-D contain gene information. Columns E-I DESeq2 outputs for translation efficiency for mock-infected samples. Columns J-N DESeq2 outputs for translation efficiency for VSV-infected samples. Supplementary Table S8. GC% and length data of MANE selected transcripts, related to Figs. 4 and 5. GC% and length for cDNA sequences, 5’-UTR, CDS and 3’-UTR. Transcripts were selected from the Matched Annotation from the NCBI and EMBL-EBI to obtain information for representative transcripts within the human transcriptome. Supplementary Table S9. Oligonucleotides used in this study. Related to Methods. List of oligos used for qRT-PCR.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.759 | 0.190 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".