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pytfmpval's Introduction

Hi, I’m Jared 👋

I’m a Senior Bioinformatics Research Scientist in Suzanne Baker’s lab in the Department of Developmental Neurobiology at St. Jude Children’s Research Hospital. We study oncohistone mutations in the context of pediatric high grade gliomas.

Other than analysis, I build useful tools and utilities for the lab and community. Recently, I created a basic utility called STRprofiler for comparing STR profiles between large collections and identifying potential sample swaps. This is particularly useful for labs that generate many cell lines/models, as we do.

Lately, I’ve been working on an R package called CRISPRball, which is largely based around a Shiny app of the same name for exploring, visualizing, and comparing CRISPR-Cas9 screens analyzed with MAGeCK. CRISPRball is now available from Bioconductor.

I am/have been involved in a handful of Bioconductor packages, including dittoSeq, SingleR, escape, and celldex.

Here’s some stats on my GitHub repos

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pytfmpval's Issues

logOddsScore in Matrix.h not affecting p-value or score

Hello,

I'm changing logOdds functions in Matrix.h, but seems that it didn't affect anything.

        // mat[k][p] = log((mat[k][p] + 0.25) /(sum + 1)) - log (background[k]); 
        mat[k][p] = 0  ; 
        // mat[k][p] = log(mat[k][p]) - log (background[k]); 

After changing the score, I re-installed python setup.py install.

It is tested on:

>>> from pytfmpval import tfmp
>>> m = tfmp.create_matrix("MA0045.pfm")
>>> tfmp.score2pval(m, 8.7737)
9.992625564336777e-06
>>> tfmp.pval2score(m, 0.00001)
8.773708000000001

Always gave the same result.

Inconsistent/intransparent score definitions

# example from README
from pytfmpval import tfmp
mat = (" 3  7  9  3 11 11 11  3  4  3  8  8  9  9 11  2"
       " 5  0  1  6  0  0  0  3  1  4  5  1  0  5  0  7"
       " 4  3  1  4  3  2  2  2  8  6  1  4  2  0  3  0"
       " 2  4  3  1  0  1  1  6  1  1  0  1  3  0  0  5"
      )
m = tfmp.read_matrix(mat)
print(tfmp.pval2score(m, 0.00001))  # 8.773708000000001
print(tfmp.score2pval(m, 8.7737))  # 9.992625564336777e-06

# my addition
print(m.minScore)  # 0
print(m.maxScore)  # 435430296

The cited paper defines the score as the sum of one element per column (representing the nucleotides).

  1. the minimal score of the matrix cannot be zero, as there are multiple columns which do not contain a zero. It is 10 (2+0+1+1+0+0+0+2+1+1+1+1+0+0+0+0).
  2. the maximal score cannot be 4.35e8, it is 132 (5+7+9+6+11+11+11+6+8+6+8+8+9+9+11+7)
  3. the score result of pval2score obviously is a different kind of score as the one given by m.minScore and m.maxScore and also different from the definition in the paper.

Can someone please clarify on the score definitions?

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