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@maxibor
Created May 10, 2022 15:00
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{
"cells": [
{
"cell_type": "markdown",
"id": "a6d55215-4651-4a9c-b1b2-e697748d3b3d",
"metadata": {},
"source": [
"## Introduction\n",
"\n",
"The task of [taxonomic profiling](https://www.sevenbridges.com/taxonomic-profiling-of-metagenomics-samples/) consists of answering the question *\"Who is there ?\"* in a metagenomic sample. \n",
"However, in practice, it turns out to be quite a challenging assignment to tackle, and many solutions have been proposed to address it (for a comparative benchmark, see [Meyer et al. 2022](https://doi.org/10.1038/s41592-022-01431-4)).\n",
"\n",
"One of the central aspect of taxonomic profiling is to distinguishing true positive (taxon actually present in a sample) from false positive (taxon actually not present in sample) taxonomic assignments.\n",
"\n",
"Today, I want to focus on one particular taxonomic profiler, [KrakenUniq](https://github.com/fbreitwieser/krakenuniq) ([Breitwieser et al. 2018](https://doi.org/10.1186/s13059-018-1568-0)).\n",
"\n",
"Based on the popular [k-mer](https://en.wikipedia.org/wiki/K-mer) based taxonomic classifier [Kraken](https://github.com/DerrickWood/kraken) ([Wood et al. 2014](https://doi.org/10.1186/gb-2014-15-3-r46)), KrakenUniq adds a unique (😉) feature of top of Kraken, the reporting of unique kmer counts. Let me explain.\n",
"\n",
"The original Kraken program is based on direct k-mer matching. Kraken builds a database of all present k-mer in each reference genomes, and then compares it the k-mers found in the query sequences/sequencing reads (fig 1) . If there is a match, it uses a taxonomic tree and the LCA algorithm to assign each query sequence to a given taxon.\n",
"\n",
"![](kraken.png) \n",
"**Figure 1**: The Kraken sequence classification algorithm. [original here](https://genomebiology.biomedcentral.com/articles/10.1186/gb-2014-15-3-r46/figures/1) \n",
"\n",
"While this is already a well performing taxonomic profiling method, it suffers from one major drawback: it can not account for duplicated sequences. For example, when reporting the number of reads belonging to each taxon in a sample, Kraken is not able to distinguish an evenly covered genome (likely a true positive) from a genome suffering from read stacking (likely a false positive), often being the symptom (fig 2) of a false positive assignment, due to reads matching ultra-conserved regions between taxons from the same clade.\n",
"\n",
"![](featured.png) \n",
"**Figure 2**: Two taxons having the same amount of assigned reads, two different scenarios. The blue genome has an evenly distributed coverage, while the purple genome suffers from read stacking. Unique kmers are highlighted with a black perimeter\n",
"\n",
"To circument this problem, KrakenUniq leverages the [HLL algorithm](https://en.wikipedia.org/wiki/HyperLogLog) to count the unique/distinc k-mers. In practice, in the example of fig 2, Kraken would have reported a \"coverage\" of 24 for both the blue and purple genome, while KrakenUniq would have reported a \"coverage\" of 7 for the blue genome, and 2 for the purple genome. \n",
"\n",
"On top of that, KrakenUniq keeps track of how many of unique k-mers have been found, out all possible unique k-mers for each genome, which gives an estimation of the \"coverage\".\n",
"\n",
"So, to summarize, with KrakenUniq, for each taxon, we now have three different metrics instead of \"just one\" for Kraken :\n",
"- read count per taxon (which we already had with kraken), we'll refer to it later as $R$\n",
"- number of unique k-mers (new with KrakenUniq), we'll refer to it later as $K$\n",
"- \"coverage\" coverage of the k-mers of the clade in the database, we'll refer to it later as $C$\n",
"\n",
"Note that I've always mentioned the \"coverage\" between quotes, this is because [KrakenUniq defines it](https://github.com/fbreitwieser/krakenuniq/blob/2ac22bf7681223efa17ffba221231c7faac9da05/src/taxdb.hpp#L1103) as $C = \\frac{k}{genome\\ size}$. \n",
"Because by definition, the maximum number of k-mers (of length $k$) for a sequence of length $L$ can not exceed $L - k + 1$. This means that in the ideal situation, for example the blue genome of fig 2, the \"coverage\" will be at best, close to 1, but never greater than 1.\n",
"\n",
"To try to make sense of these three metrics, [Guellil et al. 2022](https://doi.org/10.1186/s13059-021-02580-z) came up with a score $E$ combining them, to discriminate true positive from false positive taxonomic assignments.\n",
"\n",
"$$E = \\frac{K}{R} \\times C$$\n",
"\n",
"Here, using different simulated taxon assignment situations, I propose a tweak to this score, to try to improve its ability to differentiate true positive from false positive taxonomic assignments."
]
},
{
"cell_type": "markdown",
"id": "03596bc3-53e4-4c4a-bb6f-90a176a54fc4",
"metadata": {},
"source": [
"## The simulations"
]
},
{
"cell_type": "markdown",
"id": "fa5aee4b-aa4c-447b-b34b-d9cc0912b249",
"metadata": {},
"source": [
"First, let's define a few parameters for our simulation, and import necessary libraries"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "501627eb-d045-44ae-b236-16de00eb3de8",
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"import pandas as pd\n",
"\n",
"read_length = 45\n",
"kmer_length = 35\n",
"genome_size = 1000000"
]
},
{
"cell_type": "markdown",
"id": "20768274-3101-4f15-9a0d-4a2630277faa",
"metadata": {},
"source": [
"**We'll look at four different possible scenarios** \n",
"For each scenario, we'll simulated 100 different situations"
]
},
{
"cell_type": "markdown",
"id": "e2baf492-9fe3-405d-a060-57bc400566e3",
"metadata": {},
"source": [
"#### scenario A: high duplication, low coverage (false positive)\n",
"- A lot of reads are duplicated, probably coming from conversed regions, or sequencing artifacts\n",
"- low coverage\n",
"- There are more reads than unique kmers"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "4ea8c0e6-1561-4246-8404-e9d192d89211",
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"a_reads = np.random.randint(10, 300, 100) # randomly choose the number of reads, between 10 and 300\n",
"comp_kmer_a = lambda x: int(x / np.random.randint(2,10, 1)) # randomly choose between 2 and 10 times less k-mers\n",
"comp_kmer_a_vec = np.vectorize(comp_kmer_a)\n",
"a_kmers = comp_kmer_a_vec(a_reads)\n",
"plt.plot(a_kmers/a_reads, label=r\"$\\frac{k}{R}$\")\n",
"plt.plot(a_kmers/genome_size, label=\"cov\")\n",
"plt.title(\"scenario A\")\n",
"plt.legend(loc=\"upper left\");"
]
},
{
"cell_type": "markdown",
"id": "c1727934-7f5a-45b8-a7f1-3df71df80f6c",
"metadata": {},
"source": [
"#### scenario B: low duplication, low coverage (true positive)\n",
"- Very few reads are duplicated\n",
"- low coverage\n",
"- more unique kmers than reads (up to $ku = read\\_length - kmer\\_length + 1$ more unique k-mers than reads)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "19374503-466b-465a-8f96-beda35b2c069",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"b_reads = np.random.randint(10, 300, 100) # randomly choose the number of reads, between 10 and 300\n",
"comp_kmer_b = lambda x: min(genome_size - kmer_length + 1, int(x * np.random.randint(2,(read_length - kmer_length + 1), 1))) # randomly choose up to ku more k-mers than reads\n",
"comp_kmer_b_vec = np.vectorize(comp_kmer_b)\n",
"b_kmers = comp_kmer_b_vec(b_reads)\n",
"\n",
"plt.plot(b_kmers/b_reads, label=r\"$\\frac{k}{R}$\")\n",
"plt.plot(b_kmers/genome_size, label=\"cov\")\n",
"plt.title(\"scenario B\")\n",
"plt.legend(loc=\"upper left\");"
]
},
{
"cell_type": "markdown",
"id": "d78db714-9e20-4df1-8279-7b3d48cb72db",
"metadata": {},
"source": [
"#### scenario C: low duplication, higher coverage (true positive)\n",
"\n",
"- same as scenario B, but with a higher coverage"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "3b557177-7c28-4cc5-9667-500e39c3bb6e",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"c_reads = np.random.randint(10000, 100000, 100) # # randomly choose the number of reads, between 10000 and 100000\n",
"comp_kmer_c = lambda x: min(genome_size - kmer_length + 1, int(x * np.random.randint(2,(read_length - kmer_length + 1), 1)))\n",
"comp_kmer_c_vec = np.vectorize(comp_kmer_c)\n",
"c_kmers = comp_kmer_c_vec(c_reads)\n",
"plt.plot(c_kmers/c_reads, label=r\"$\\frac{k}{R}$\")\n",
"plt.plot(c_kmers/genome_size, label=\"cov\")\n",
"plt.title(\"scenario C\")\n",
"plt.legend(loc=\"upper left\");"
]
},
{
"cell_type": "markdown",
"id": "bab25946-c314-41e5-bd03-a1e238f74e11",
"metadata": {},
"source": [
"#### scenario D: low duplication, high coverage\n",
"- more reads than unique kmers (because of the coverage definiton of KrakenUniq)\n",
"- high coverage"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "d019e693-0a45-4224-902b-e63626896f78",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"d_reads = np.random.randint(genome_size*1.1, genome_size*3, 100) # getting between 1.1*genome_size and 3*genome size reads\n",
"comp_kmer_d = lambda x: min(genome_size - kmer_length + 1, int(x * np.random.randint(2,(read_length - kmer_length + 1), 1)))\n",
"comp_kmer_d_vec = np.vectorize(comp_kmer_d)\n",
"d_kmers = comp_kmer_d_vec(d_reads)\n",
"plt.plot(d_kmers/d_reads, label=r\"$\\frac{k}{R}$\")\n",
"plt.plot(d_kmers/genome_size, label=\"cov\")\n",
"plt.title(\"scenario D\")\n",
"plt.legend(loc=\"upper left\");"
]
},
{
"cell_type": "markdown",
"id": "5075bf41-39d4-4474-a876-ccd13b3c6edc",
"metadata": {},
"source": [
"## Comparing E-scores"
]
},
{
"cell_type": "markdown",
"id": "151ae77e-1ca2-49ea-af11-5489434c0c55",
"metadata": {},
"source": [
"### Guellil *et al.* E-score "
]
},
{
"cell_type": "markdown",
"id": "2f21fa17-68ed-42df-8b88-63b8557c0236",
"metadata": {},
"source": [
"Now that we have our four different scenarios, let's look at how [Guellil *et al.*](https://doi.org/10.1186/s13059-021-02580-z) E-score performs at discriminating between true positive (scenario A) and false positive (scenario B, C, and D) taxonomic assignments."
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "7eb6175e-d9ff-43f4-bd54-d3751a4add5a",
"metadata": {},
"outputs": [],
"source": [
"def e_score_guellil(nb_kmer, nb_read, genome_size):\n",
" cov = nb_kmer/genome_size\n",
" \n",
" return((nb_kmer/nb_read) * cov )\n",
"e_score_guellil_vec = np.vectorize(e_score_guellil)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "ec948092-f46f-48f5-8812-8645a886c9d5",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"e_score_guellil_a = e_score_guellil_vec(a_kmers, a_reads, genome_size)\n",
"e_score_guellil_b = e_score_guellil_vec(b_kmers, b_reads, genome_size)\n",
"e_score_guellil_c = e_score_guellil_vec(c_kmers, c_reads, genome_size)\n",
"e_score_guellil_d = e_score_guellil_vec(d_kmers, d_reads, genome_size)\n",
"\n",
"plt.plot(e_score_guellil_a, label = \"scenario A\")\n",
"plt.plot(e_score_guellil_b, label = \"scenario B\")\n",
"plt.plot(e_score_guellil_c, label = \"scenario C\")\n",
"plt.plot(e_score_guellil_d, label = \"scenario D\")\n",
"plt.legend(loc=\"upper left\")\n",
"plt.title(\"Guellil et al. E score\")\n",
"plt.ylim(0,0.001);"
]
},
{
"cell_type": "markdown",
"id": "1167124f-0fa8-4629-961f-6d51322e0451",
"metadata": {},
"source": [
"As we can see, it can be quite tricky in some situations to differentiate a true from a false positive assignment. This is particularly problematic beween scenario A and scenario B."
]
},
{
"cell_type": "markdown",
"id": "ed18456d-3fcf-40a9-9ed5-6bf4c8d00a52",
"metadata": {},
"source": [
"### Modified *dexp* E-score\n",
"Here I propose a slightly different score to mitigate some of issue.\n",
"Instead of defining \n",
"\n",
"$$E = \\frac{K}{R}\\times C$$\n",
"\n",
"I propose to use \n",
"\n",
"$$E = \\frac{K}{R} \\times dexp(C)$$\n",
"\n",
"with $dexp$ being the [double exponential function](https://en.wikipedia.org/wiki/Double_exponential_function).\n",
"\n",
"This way, more emphasis is given to the \"coverage\", which particularly helps in low \"coverage\" scenarios, since the double exponential function grows \"really fast\" between 0 and 1."
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "ab1a6652-32af-4867-b7b1-770514ef4d1e",
"metadata": {},
"outputs": [],
"source": [
"#https://en.wikipedia.org/wiki/Double_exponential_function\n",
"def double_exp(x, a=1.3, b=18):\n",
" return(a**(b*x))\n",
"double_exp_vec = np.vectorize(double_exp) "
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "fe4c1e4e-8c54-4ba1-bb02-c4c8044c811e",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"x = np.arange(0,1,0.01)\n",
"y = double_exp_vec(x)\n",
"plt.plot(x, y)\n",
"plt.title(\"Double exponential function\");"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "e0fbf720-542d-45b7-aebf-ef2c1e3de94b",
"metadata": {},
"outputs": [],
"source": [
"def e_score_dexp(nb_kmer, nb_read, genome_size):\n",
" cov = nb_kmer/genome_size\n",
" \n",
" return((nb_kmer/nb_read) * double_exp(cov))\n",
"e_score_dexp_vec = np.vectorize(e_score_dexp)"
]
},
{
"cell_type": "markdown",
"id": "514ddbdb-572d-40cc-afe4-68103003d603",
"metadata": {},
"source": [
"Now let's look at how this modified E-score performs "
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "ebb06464-0a35-4f63-b3bf-528a9f05db00",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"e_score_dexp_a = e_score_dexp_vec(a_kmers, a_reads, genome_size)\n",
"e_score_dexp_b = e_score_dexp_vec(b_kmers, b_reads, genome_size)\n",
"e_score_dexp_c = e_score_dexp_vec(c_kmers, c_reads, genome_size)\n",
"e_score_dexp_d = e_score_dexp_vec(d_kmers, d_reads, genome_size)\n",
"\n",
"plt.plot(e_score_dexp_a, label = \"case_a\")\n",
"plt.plot(e_score_dexp_b, label = \"case_b\")\n",
"plt.plot(e_score_dexp_c, label = \"case_c\")\n",
"plt.plot(e_score_dexp_d, label = \"case_b\")\n",
"plt.legend(loc=\"upper left\")\n",
"plt.title(\"Double-exp E-score\")\n",
"\n",
"plt.ylim(0,4);"
]
},
{
"cell_type": "markdown",
"id": "d6eb075d-cb4d-433d-a9ee-8d3242c3eab4",
"metadata": {},
"source": [
"We can see that there is a much clearer distinction between true and false positive assignments.\n",
"We can also look at the mean difference of all scenarios between true and false positives, for the original, and the new double exp E-score"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "e8c9f770-4809-4b68-a64f-406161d2dd08",
"metadata": {},
"outputs": [],
"source": [
"diff_e_score_guellil = np.mean([e_score_guellil_b - e_score_guellil_a, e_score_guellil_c - e_score_guellil_a, e_score_guellil_d - e_score_guellil_a], axis=0)\n",
"diff_e_score_dexp = np.mean([e_score_dexp_b - e_score_dexp_a, e_score_dexp_c - e_score_dexp_a, e_score_dexp_d - e_score_dexp_a], axis=0)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "464c545e-35c7-4176-ae2a-4b9b1efc3c49",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(diff_e_score_guellil, label=\"Guellil et al. E-score\")\n",
"plt.plot(diff_e_score_dexp, label=\"double-exp E-score\")\n",
"plt.title(\"Diffence of E-score between true and false positive\\n(the greater the better)\")\n",
"plt.legend(loc=\"upper left\")\n",
"plt.ylim(0,30);"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "39cd17ed-c446-4199-9959-0c15c27a0196",
"metadata": {},
"outputs": [],
"source": [
"df = pd.DataFrame(list(zip(diff_e_score_guellil, diff_e_score_dexp)), columns=['Guellil et al.', 'dexp'])"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "a53838e7-a3b1-483f-9633-b712631b6636",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"sns.boxplot(data=df)\n",
"plt.title(\"Diffence of E-score between true and false positive\\n(the greater the better)\");"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "15e93c8a-604b-4365-9ce6-b62a0099adb3",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Guellil et al. 1.012888\n",
"dexp 50.104112\n",
"dtype: float64"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.mean(axis=0)"
]
},
{
"cell_type": "markdown",
"id": "bee9cf3c-a19a-4f17-bc6d-02f96a963be0",
"metadata": {},
"source": [
"We can see that on average between all scenarios, for Guellil *et al.* E-score, there is only a difference of `1` points, while for the modified double-exponential E-score, there is an average difference of `50` points."
]
},
{
"cell_type": "markdown",
"id": "c811817c-a7b7-4eef-a755-4442311bc029",
"metadata": {},
"source": [
"### Conclusion"
]
},
{
"cell_type": "markdown",
"id": "a927d8d8-3746-4097-8808-52ff560c2235",
"metadata": {},
"source": [
"In my simulations, using a the modified double-exponential E-score could allow for a better distinction between true and false positive taxonomic assignations by KrakenUniq"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python [conda env:root] *",
"language": "python",
"name": "conda-root-py"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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