identifications_over_time.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import altair as alt \n",
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "file = r'.\\Working_Datafiles\\All_N_Glycopeptides.csv'\n",
    "df = pd.read_csv(file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
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\"master_protein_accessions\": \"P12763\", \"rt_min\": 65.7695, \"mz_da\": 1315.87683, \"charge\": 3, \"delta_mz_da\": 0.00092, \"theo_mh_da\": 3945.61319, \"delta_m_ppm\": 0.7, \"num_psms\": 42, \"glycan_composition\": \"HexNAc(4)Hex(5)NeuAc(2)\", \"confidence.1\": \"High\", \"byonic_score\": 563.2, \"delta_byonic_score\": 517.2, \"log_prob\": 7.67, \"delta_mod_score\": 517.2, \"q_value_1d\": 2.8550713000884402e-09, \"q_value_2d\": 2.0214577854693503e-09, \"fdr_1d\": 0.0, \"fdr_2d\": 0.0, \"pep_1d\": 3.02947390934584e-08, \"pep_2d\": 2.1449389499793e-08, \"num_protein_groups\": 1, \"num_proteins\": 1, \"off_by_x\": 0, \"position_in_protein\": 145, \"num_missed_cleavages\": 0, \"peptide_group_fdr_2d\": 0.0, \"peptide_group_fdr_1d\": 0.0, \"positions_in_master_proteins\": \"P12763 [145-159]\", \"modifications_in_master_proteins\": null, \"sequence_in_protein\": \"K.LCPDCPLLAPLNDSR.V\", \"positions_in_proteins\": \"[145-159]\", \"sequence\": \"LCPDCPLLAPLNDSR\", \"data_source\": \"1_45C_Run2\", \"temperature\": \"45C\", \"run\": \"Run2\", \"concentration\": 1.0, \"dilution\": \"1x\", \"glycan\": \"HexNAc(4)Hex(5)NeuAc(2)\", \"glycan_type\": \"Sialylated\", \"degree_sial\": \"Disialylated\", \"pep_mods\": \"LCPDCPLLAPLNDSR_HexNAc(4)Hex(5)NeuAc(2)\"}, {\"accession\": \"P12763\", \"description\": \"Alpha-2-HS-glycoprotein OS=Bos taurus OX=9913 GN=AHSG PE=1 SV=2\", \"checked\": true, \"confidence\": \"High\", \"annotated_sequence\": \"[K].LCPDCPLLAPLNDSR.[V]\", \"modifications\": \"2xCarbamidomethyl [C2; C5]; 1xHexNAc(5)Hex(6)NeuAc(2) [N12]\", \"master_protein_accessions\": \"P12763\", \"rt_min\": 57.1867, \"mz_da\": 1437.58569, \"charge\": 3, \"delta_mz_da\": -0.00095, \"theo_mh_da\": 4310.74539, \"delta_m_ppm\": -0.66, \"num_psms\": 74, \"glycan_composition\": \"HexNAc(5)Hex(6)NeuAc(2)\", \"confidence.1\": \"High\", \"byonic_score\": 403.5, \"delta_byonic_score\": 403.5, \"log_prob\": 6.76, \"delta_mod_score\": 360.9, \"q_value_1d\": 2.67997189629473e-08, \"q_value_2d\": 1.89748332470086e-08, \"fdr_1d\": 0.0, \"fdr_2d\": 0.0, \"pep_1d\": 2.47788329808149e-07, \"pep_2d\": 1.75439987016858e-07, \"num_protein_groups\": 1, \"num_proteins\": 1, \"off_by_x\": 0, \"position_in_protein\": 145, \"num_missed_cleavages\": 0, \"peptide_group_fdr_2d\": 0.0, \"peptide_group_fdr_1d\": 0.0, \"positions_in_master_proteins\": \"P12763 [145-159]\", \"modifications_in_master_proteins\": null, \"sequence_in_protein\": \"K.LCPDCPLLAPLNDSR.V\", \"positions_in_proteins\": \"[145-159]\", \"sequence\": \"LCPDCPLLAPLNDSR\", \"data_source\": \"1_45C_Run2\", \"temperature\": \"45C\", \"run\": \"Run2\", \"concentration\": 1.0, \"dilution\": \"1x\", \"glycan\": \"HexNAc(5)Hex(6)NeuAc(2)\", \"glycan_type\": \"Sialylated\", \"degree_sial\": \"Disialylated\", \"pep_mods\": \"LCPDCPLLAPLNDSR_HexNAc(5)Hex(6)NeuAc(2)\"}], \"data-d2dc17c6fb9bf769958d761c9c597846\": [{\"time\": -18.3, \"buffer_b\": 3}, {\"time\": 0.0, \"buffer_b\": 3}, {\"time\": 81.7, \"buffer_b\": 35}, {\"time\": 82.7, \"buffer_b\": 75}, {\"time\": 91.7, \"buffer_b\": 75}, {\"time\": 92.2, \"buffer_b\": 95}, {\"time\": 101.7, \"buffer_b\": 95}, {\"time\": 102.7, \"buffer_b\": 3}, {\"time\": 117.7, \"buffer_b\": 3}]}}, {\"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.HConcatChart(...)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grad_time = [0, 18.3, 100, 101, 110, 110.5, 120, 121, 136]\n",
    "grad_b = [3, 3, 35, 75, 75, 95, 95, 3, 3]\n",
    "\n",
    "gradient = pd.DataFrame({'time':grad_time, 'buffer_b':grad_b})\n",
    "gradient['time'] -= 18.3\n",
    "\n",
    "line = alt.Chart(gradient).mark_line(color='black', strokeDash=[5, 5]).encode(\n",
    "    x=alt.X('time:Q', title='Time (min)'),\n",
    "    y=alt.Y('buffer_b:Q', title='%B')\n",
    ")\n",
    "\n",
    "peptides = df[(df.concentration==1)].drop_duplicates(['pep_mods', 'temperature'])\n",
    "\n",
    "bars = alt.Chart(peptides).mark_bar().encode(\n",
    "    x=alt.X('rt_min:Q', title='', bin=alt.Bin(extent=[0, 120], step=10)),\n",
    "    y=alt.Y('count()')\n",
    ")\n",
    "\n",
    "chart = alt.HConcatChart()\n",
    "for temp in peptides.temperature.unique():\n",
    "    b = bars.transform_filter(alt.datum.temperature==temp)\n",
    "    chart |= (b+line).properties(title=temp)\n",
    "\n",
    "chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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