{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Using Metadensity with PAR-CLIP\n", "This notebook showcases use cases on PAR-CLIP" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "please set the right config according to genome coordinate\n", "Using /home/hsher/gencode_coords/GRCh38.p13.genome.fa\n", "Using: /home/hsher/gencode_coords/gencode.v33.transcript.gff3\n" ] } ], "source": [ "# set up files associated with each genome coordinates\n", "import metadensity as md\n", "md.settings.from_config_file('/home/hsher/projects/Metadensity/config/hg38.ini')\n", "\n", "\n", "# then import the modules\n", "from metadensity.metadensity import *\n", "from metadensity.plotd import *\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "\n", "# I have a precompiles list of ENCODE datas as a csv that loads in this dataloader\n", "import sys\n", "sys.path.append('/home/hsher/projects/Metadensity/scripts')\n", "\n", "plt.style.use('seaborn-white')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## I downloaded some PAR-CLIP from the internet.\n", "[Link to GEO](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE150925)\n", "\n", "They offer only the IP bigwig. So here there is no way to perform background control" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "from pathlib import Path\n", "indir = Path('/home/hsher/scratch/parclip_data')\n", "\n", "ip_rep1 = str(indir/'GSM4561069_HEK293_PARCLIP_YBX1.bw')\n", "ip_rep2 = str(indir/'GSM4561069_HEK293_PARCLIP_YBX1.bw')\n", "\n", "igg_rep1 = str(indir/'GSM4561069_HEK293_PARCLIP_YBX1.bw')\n", "igg_rep2 = str(indir/'GSM4561069_HEK293_PARCLIP_YBX1.bw')\n", "\n", "data = {'minus_0':ip_rep1,\n", " 'plus_0':ip_rep1, # data on GEO is not processed in a strand specific manner\n", " 'minus_1': ip_rep2,\n", " 'plus_1': ip_rep2,\n", " 'minus_control_0': igg_rep1,\n", " 'plus_control_0': igg_rep1,\n", " 'minus_control_1':igg_rep2,\n", " 'plus_control_1':igg_rep2,\n", " 'RBP': 'YBX1',\n", " 'uid': 'YBX1'\n", "}\n", "\n", "data_series = pd.Series(data)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "minus_0 True\n", "plus_0 True\n", "minus_1 True\n", "plus_1 True\n", "minus_control_0 True\n", "plus_control_0 True\n", "minus_control_1 True\n", "plus_control_1 True\n", "RBP False\n", "uid False\n", "dtype: bool" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data_series.apply(os.path.isfile)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "warning no bam file!\n", "warning no bam file!\n", "warning no bam file!\n", "warning no bam file!\n" ] } ], "source": [ "parclip = eCLIP.from_series(data_series)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "clips = [parclip]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Calulcate Density and Truncation sites\n", "Object `Metatruncation` and `Metadensity` takes three things:\n", "1. an experiment object `eCLIP` or `STAMP`.\n", "2. a set of transcript pyBedTools that you want to plot on\n", "3. name of the object\n", "\n", "Options include:\n", "1. `sample_no=` allows you to decide how many transcript you want to build the density. It will take longer. By default, `sample_no=200`. So in transcript if you give more than 200 transcripts, only 200 will be used\n", "2. `metagene` allows you to use pre-built metagene. This feature is more useful when you want to compare the same set of RNA over many RBPs.\n", "3. `background_method` handles how you want to deal with IP v.s. Input\n", "4. `normalize` handles how you want to normalize values within a transcript.\n", "\n", "## Difference between truncation and density\n", "\n", "`Metadensity` represents read coverage. `Metatruncation` represents the 5' end of read 2 for `eCLIP`; edit sites for `STAMP`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Now we need to decide a set of transcripts to plot the metagene: \n", "\n" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "binding_site = BedTool(indir/'GSM4561069_HEK293_PARCLIP_YBX1_Bmix-binding-sites.tsv')\n", "transcript_w_peak = transcript.intersect(binding_site, s = True)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Using: /home/hsher/projects/Metadensity/metadensity/data/hg38/gencode\n", "Done building metagene\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/projects/ps-yeolab3/hsher/Metadensity/metadensity/metadensity.py:932: RuntimeWarning: invalid value encountered in true_divide\n", " values = values/np.sum(values)\n", "/projects/ps-yeolab3/hsher/Metadensity/metadensity/metadensity.py:989: RuntimeWarning: Mean of empty slice\n", " feature_average = np.nanmean(np.stack(all_feature_values), axis = 0)\n" ] } ], "source": [ "# this step takes some time for building metagene from the annotation files.\n", "p300_targets_meta = Metadensity(parclip, 'YBX1 PAR-CLIP',\n", " transcripts = transcript_w_peak,\n", " background_method = None, \n", " normalize = True)\n", "p300_targets_meta.get_density_array()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Visualize RBP map: individual density per transcript\n", "\n", "use `feature_to_show` to decide what features to show. " ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/projects/ps-yeolab3/hsher/Metadensity/metadensity/plotd.py:166: RuntimeWarning: Mean of empty slice\n", " density_concat = np.nanmean(np.stack([den_arr[feat,align, r] for r in metaden_object.eCLIP.rep_keys]), axis = 0)\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "### PLOT INDIVIDUAL DENSITY\n", "# you can customize the list of features you want to show. This is suitable when you are looking for splicing\n", "f = plot_rbp_map([p300_targets_meta], features_to_show = generic_rna, ymax = 0.0002)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'mean relative information')" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "f=plot_mean_density([p300_targets_meta],\n", " features_to_show = protein_coding)\n", "f=beautify(f, offset = 0) # sns.despine \n", "f.get_axes()[0].set_ylabel('mean relative information')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "metadensity", "language": "python", "name": "metadensity" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.12" } }, "nbformat": 4, "nbformat_minor": 4 }