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sci-moTF
sci-moTF is a very simple package to help with finding motifs that are enriched in different clusters, that are also expressed in your dataset and make it easier to draw inferences on which TFs may be driving the observed changes.
The input to scimotf is: 1) the output of FIMO , fimo.tsv, 2) a csv file with gene identifier (e.g. name), cluster, log2FC, and p-value.
Example format for fimo.tsv
motif_id motif_alt_id sequence_name start stop strand score p-value q-value matched_sequence
SP5_MOUSE.H11MO.0.C Gh 1668 1691 - 32.7879 9.78e-16 4e-09 GGGGGGGAGGGGGAGGGGGAGGGG
Example format for cluster.csv
gene_name,cluster,log2FC,padj
Hoxa9,hindbrain,-2.8,0.00031
sci-TF will output two files, 1) scitf_detailed.csv, and 2) scitf_summary.csv.
sictf_motif_merged_fp-0.05_cp-1.0.csv
This gives a detailed output of each TF that was potentially able to bind to genes in a cluster.
cluster,motif,p-value,q-value,odds-ratio,count-genes-in-cluster,count-genes-bg,remainder-cluster,remainder-bg,tf-log2FC,tf-padj,tf-cluster,%-coverage,genes
Overview
- Filter fimo.tsv and remove any motifs that don't meet the p or qvalue threshold
- Filter any motifs in fimo.tsv that don't exist in the users input data (have a 0 logFC)
- For each TF for each cluster, count how many genes exist and perform a FET w.r.t the background
- adjust p-values
- summarise the identified TFs
Please post questions and issues related to sci-moTF on the Issues page_
section of the GitHub repository.
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