{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Measuring Transcription Rate in *Drosophila* embryos" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "(c) 2016 Griffin Chure. This work is licensed under a [Creative Commons Attribution License CC-BY 4.0](https://creativecommons.org/licenses/by/4.0/). All code contained herein is licensed under an [MIT license](https://opensource.org/licenses/MIT)." ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "import glob\n", "import skimage.io\n", "import skimage.filters\n", "import skimage.morphology\n", "\n", "# The following line is for use in this notebook only and should not be used in \n", "# a script\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "These data come from [Garcia et al. 2013](http://www.sciencedirect.com/science/article/pii/S0960982213011135) and were generously made available by Hernan Garcia directly. In this exercise, we will measure the rate of transcription in a nuclear cycle 14 of a developing *Drosophila melanogaster* embryo. Specificially, we are watching the beginning and end of transcription of the [Hunchback](https://en.wikipedia.org/wiki/Drosophila_embryogenesis#Maternal_effect_genes) morphogen. This was done in a particularly clever way by using the MS2 system to tag the 5' and 3' ends of the mRNA in *separate embryos*. In this experimental systems, fluorescent puncta appear when that region of the mRNA is properly transcribed. By watching the appearance of the relevant spots, we can make a measurement of the rate of transcription and investigate whether the timing makes sense, given the time in between nuclear divisions." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Developing an image processing pipeline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Before we can reach any quantitative biological conclusions, we first need to establish some way of measuring the number of spots in each image. Since we will have a (relatively) large image set, it is imperative that we perform this procedure without requiring any manual intervention. To begin, let's take a look at a few representative images and come up with a segmentation scheme. \n", "\n", "\n", "