|
| 1 | +###################### |
| 2 | +# Import libraries |
| 3 | +###################### |
| 4 | + |
| 5 | +import pandas as pd |
| 6 | +import streamlit as st |
| 7 | +import altair as alt |
| 8 | +from PIL import Image |
| 9 | + |
| 10 | +###################### |
| 11 | +# Page Title |
| 12 | +###################### |
| 13 | + |
| 14 | +image = Image.open('dna-logo.jpg') |
| 15 | + |
| 16 | +st.image(image, use_column_width=True) |
| 17 | + |
| 18 | +st.write(""" |
| 19 | +# DNA Nucleotide Count Web App |
| 20 | +
|
| 21 | +This app counts the nucleotide composition of query DNA! |
| 22 | +
|
| 23 | +*** |
| 24 | +""") |
| 25 | + |
| 26 | + |
| 27 | +###################### |
| 28 | +# Input Text Box |
| 29 | +###################### |
| 30 | + |
| 31 | +#st.sidebar.header('Enter DNA sequence') |
| 32 | +st.header('Enter DNA sequence') |
| 33 | + |
| 34 | +sequence_input = ">DNA Query 2\nGAACACGTGGAGGCAAACAGGAAGGTGAAGAAGAACTTATCCTATCAGGACGGAAGGTCCTGTGCTCGGG\nATCTTCCAGACGTCGCGACTCTAAATTGCCCCCTCTGAGGTCAAGGAACACAAGATGGTTTTGGAAATGC\nTGAACCCGATACATTATAACATCACCAGCATCGTGCCTGAAGCCATGCCTGCTGCCACCATGCCAGTCCT" |
| 35 | + |
| 36 | +#sequence = st.sidebar.text_area("Sequence input", sequence_input, height=250) |
| 37 | +sequence = st.text_area("Sequence input", sequence_input, height=250) |
| 38 | +sequence = sequence.splitlines() |
| 39 | +sequence = sequence[1:] # Skips the sequence name (first line) |
| 40 | +sequence = ''.join(sequence) # Concatenates list to string |
| 41 | + |
| 42 | +st.write(""" |
| 43 | +*** |
| 44 | +""") |
| 45 | + |
| 46 | +## Prints the input DNA sequence |
| 47 | +st.header('INPUT (DNA Query)') |
| 48 | +sequence |
| 49 | + |
| 50 | +## DNA nucleotide count |
| 51 | +st.header('OUTPUT (DNA Nucleotide Count)') |
| 52 | + |
| 53 | +### 1. Print dictionary |
| 54 | +st.subheader('1. Print dictionary') |
| 55 | +def DNA_nucleotide_count(seq): |
| 56 | + d = dict([ |
| 57 | + ('A',seq.count('A')), |
| 58 | + ('T',seq.count('T')), |
| 59 | + ('G',seq.count('G')), |
| 60 | + ('C',seq.count('C')) |
| 61 | + ]) |
| 62 | + return d |
| 63 | + |
| 64 | +X = DNA_nucleotide_count(sequence) |
| 65 | + |
| 66 | +#X_label = list(X) |
| 67 | +#X_values = list(X.values()) |
| 68 | + |
| 69 | +X |
| 70 | + |
| 71 | +### 2. Print text |
| 72 | +st.subheader('2. Print text') |
| 73 | +st.write('There are ' + str(X['A']) + ' adenine (A)') |
| 74 | +st.write('There are ' + str(X['T']) + ' thymine (T)') |
| 75 | +st.write('There are ' + str(X['G']) + ' guanine (G)') |
| 76 | +st.write('There are ' + str(X['C']) + ' cytosine (C)') |
| 77 | + |
| 78 | +### 3. Display DataFrame |
| 79 | +st.subheader('3. Display DataFrame') |
| 80 | +df = pd.DataFrame.from_dict(X, orient='index') |
| 81 | +df = df.rename({0: 'count'}, axis='columns') |
| 82 | +df.reset_index(inplace=True) |
| 83 | +df = df.rename(columns = {'index':'nucleotide'}) |
| 84 | +st.write(df) |
| 85 | + |
| 86 | +### 4. Display Bar Chart using Altair |
| 87 | +st.subheader('4. Display Bar chart') |
| 88 | +p = alt.Chart(df).mark_bar().encode( |
| 89 | + x='nucleotide', |
| 90 | + y='count' |
| 91 | +) |
| 92 | +p = p.properties( |
| 93 | + width=alt.Step(80) # controls width of bar. |
| 94 | +) |
| 95 | +st.write(p) |
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