shell scripts, R scripts, and data required to reproduce the main analyses in Sokolowski et al., 2023
Bibliographic record
Abstract
These directories contain the scripts (shell and R) and data required for the primary analysis of Sokolowski et al., 2023. Title: Transcriptomic effects of the foraging gene shed light on pathways of pleiotropy and plasticity. Athors: Authors: Dustin J. Sokolowski1,2*, Oscar E. Vasquez3*, Michael D. Wilson1,2, Marla B. Sokolowski3,4, Ina Anreiter5 <br> Author Affiliations *Authors contributed equally 1Genetics and Genome Biology, SickKids Research Institute, Toronto, ON, Canada 2Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada 3Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada 4Program in Child and Brain Development, Canadian Institute for Advanced Research, ON, Canada. 5Department of Biological Sciences, University of Toronto Scarborough, Toronto, ON, Canada Corresponding Author For Manuscript: ina-dot-anreiter-at-utoronto-dot-ca Data analysis and figshare generator: dustin-dot-sokolowski-at-sickkids-dot-ca - alternative email (for when moved on from PhD) - djsokolowski95-at-gmail-dot-com <br> Each folder has it's own readme explaining the contents within. Directories have not been changed. Therefore to re-generate any output, they would need to be switched for the indivudal The raw and processed data (outside of the fastq, bw, and bam files) to regenerate the major analyses of each paper are the in /data subdirectory already. This includes all of the DEGs, pathways, varimax genes, scMappR outputs, SNP vcf files etc. <br> The sequencing information associated with these data can be found on arrayexpress https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-12688?query=foraging <br> R packages used: - scMappR - DESeq2 - gplots - edgeR - reshape2 - ggplot2 - TxDb.Dmelanogaster.UCSC.dm6.ensGene - org.Dm.eg.db - ChIPseeker - ggfortify - scales - xlsx - ActivePathways - DEET - Seurat - WGCNA - pheatmap - gProfileR - dplyr - reshape <br> Genomics command-line modules used: - fastqc - STAR - trimmomatic - bwa - samtools - bedtools - bcftools - gatk (picard) - featurecounts - qualimap - DeepTools <br> <br>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.012 | 0.015 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.018 |
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; both teacher heads agree on what is shown here.
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".