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Table 1 A linear model based on transcript expression and length predicts a substantial proportion of Fmrp HITS-CLIP data

From: Fmrp targets or not: long, highly brain-expressed genes tend to be implicated in autism and brain disorders

Linear model Fmrp count >1 Fmrp count >16
n= 7,207 genes n= 1,228 genes
r 2 r 2 p
Fmrp count ~ transcript abundance 0.41 0.21 p < 2.2e − 16
Fmrp count ~ Cds length 0.21 0.12 p < 2.2e − 16
Fmrp count ~ transcript length 0.23 0.09 p < 2.2e − 16
Fmrp count ~ abundance + length (either) 0.54 0.44 p < 2.2e − 16
Fmrp count ~ abundance + Cds length + transcript length 0.61 0.44 p < 2.2e − 16
  1. Using either all genes with at least one CLIP read, expression (logCPM) or length (also log2) predicts some of the Fmrp CLIP tag depth (left column). A linear model incorporating all three has an r 2 > 0.6. Limiting the analysis only to those genes with high read count (>16), the model still has an r 2 > 0.4. All models are highly significant (P < 2.2e − 16).