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qpcr-pipeline's Introduction

Real-Time PCR (qPCR) Pipeline

Auto-analysis for Real-Time PCR (qPCR) data.

This qPCR experiment usually have two group: Control (CK) and sample, and at least two type genes: Housekeeping Gene (HG) and Target Gene (TG). In our lab this usually label with ub7 and ve.

Congratulations! A alternative way to analysis of qPCR data can be find in : A shiny for analysis qRT-PCR data

1. Dependencies

  • python
    • collections
    • itertools
    • csv
    • pandas
    • numpy
    • sys
  • R
    • ggplot2
    • gridExtra
    • ggthemes
    • ggsci
    • reshape2
    • dplyr

2. INPUT

There is a example input data in Example_data/.

3. USAGE

./qPCR.sh A B C D E F

Argument:

  • A: absolute path of Input data (e, /public/home/hope/qPCR)
  • B: Input Data (e, raw_input_qPCR.csv)
  • C: Width of output pdf file
  • D: Height of output pdf file
  • E: Whether plot a scientific journals figure using the ggsci packages (yes or no)
  • F: The sample name used as reference level in ANOVA analysis

Running on the example data:

./qPCR.sh /public/home/hope/qPCR raw_input_qPCR.csv 18 8 no CK

4. OUTPUT

  • raw_input_qPCR_ubq7.csv
  • raw_input_qPCR_ve.csv
  • RQraw_input_qPCR_ve.csv
  • RQraw_input_qPCR_ubq7.csv
  • raw_input_qPCR_R.csv
  • raw_input_qPCR_ANOVA.csv
  • Pro_raw_input_qPCR_R.csv
  • Pro_raw_input_qPCR.pdf
  • raw_input_qPCR_T-test.pdf

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