JPWO2021226285A5 - Equalizer-Based Intensity Correction for Base Calling - Google Patents

Equalizer-Based Intensity Correction for Base Calling Download PDF

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JPWO2021226285A5
JPWO2021226285A5 JP2022567386A JP2022567386A JPWO2021226285A5 JP WO2021226285 A5 JPWO2021226285 A5 JP WO2021226285A5 JP 2022567386 A JP2022567386 A JP 2022567386A JP 2022567386 A JP2022567386 A JP 2022567386A JP WO2021226285 A5 JPWO2021226285 A5 JP WO2021226285A5
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ベースコールのコンピュータ実装方法であって、前記コンピュータ実装方法は、
画像にアクセスすることであって、前記画像のピクセルは、ターゲットクラスターからの強度放射及び追加の隣接クラスターからの強度放射を示す、アクセスすることと、
信号対ノイズ比を増加させるように構成されているピクセル係数を含むルックアップテーブルをルックアップテーブルのバンクから選択することと、
前記ピクセル係数を前記画像中の前記ピクセルの強度値に適用し、出力を生成することと、
前記ターゲットクラスターを前記出力に基づいてベースコールすることと、を含む、コンピュータ実装方法。 1. A computer-implemented method for base calling, the computer-implemented method comprising:
accessing an image, the pixels of the image indicating intensity radiation from a target cluster and intensity radiation from additional adjacent clusters;
selecting a lookup table from a bank of lookup tables that includes pixel coefficients configured to increase a signal to noise ratio;
applying the pixel coefficients to intensity values of the pixels in the image to generate an output;
and base calling the target clusters based on the output. 前記ピクセル係数が、畳み込み演算を使用して前記強度値に適用される、請求項１に記載のコンピュータ実装方法。The computer-implemented method of claim 1 , wherein the pixel coefficients are applied to the intensity values using a convolution operation. 前記ピクセル係数が、補間演算を使用して前記強度値に適用される、請求項１に記載のコンピュータ実装方法。The computer-implemented method of claim 1 , wherein the pixel coefficients are applied to the intensity values using an interpolation operation. 前記信号対ノイズ比において増加する信号は、前記ターゲットクラスターからの前記強度放射であり、前記信号対ノイズ比において減少するノイズは、前記追加の隣接クラスターからの前記強度放射に追加のノイズ源を加えたものである、請求項１に記載のコンピュータ実装方法。 2. The computer-implemented method of claim 1, wherein the signal that increases in the signal-to-noise ratio is the intensity radiation from the target cluster and the noise that decreases in the signal-to-noise ratio is the intensity radiation from the additional adjacent clusters plus additional noise sources. 前記ピクセルは、前記ターゲットクラスターの中心を含む中心ピクセルを含み、前記ピクセル内の各ピクセルは、複数のサブピクセルに分割可能である、請求項１に記載のコンピュータ実装方法。 The computer-implemented method of claim 1 , wherein the pixels include a central pixel that includes a center of the target cluster, and each pixel within the central pixel is divisible into a number of sub-pixels. 選択された前記ルックアップテーブルが、サブピクセルルックアップテーブであり、ルックアップテーブルの前記バンクが、複数のサブピクセルルックアップテーブルである、請求項１に記載のコンピュータ実装方法。2. The computer-implemented method of claim 1, wherein the selected lookup table is a sub-pixel lookup table and the bank of lookup tables is a plurality of sub-pixel lookup tables. 前記ターゲットクラスターの中心を含む中心ピクセルの複数のサブピクセルのうちの特定のサブピクセルに応じて、サブピクセルルックアップテーブルの前記バンクから、前記特定のサブピクセルに対応する前記サブピクセルルックアップテーブルを選択することであって、選択された前記サブピクセルルックアップテーブルは、前記ピクセル係数を含む、選択することと、
前記画像中の前記ピクセルの前記強度値に対して、前記ピクセル係数を要素ごとに乗算し、前記要素ごとの乗算の積を合計して前記出力を生成することであって、前記ピクセル係数は、重みとして機能し、前記出力は、前記強度値の重み付き和である、生成することと、
前記出力を使用して、前記ターゲットクラスターをベースコールすることであって、複数の撮像チャネルにおける各撮像チャネルの前記出力を生成することと、各撮像チャネルの前記出力を使用して前記ターゲットクラスターをベースコールすることと、を含む、ベースコールすることと、を更に含む、請求項６に記載のコンピュータ実装方法。 selecting, in response to a particular subpixel among a plurality of subpixels of a central pixel including a center of the target cluster, from the bank of subpixel lookup tables, the subpixel lookup table corresponding to the particular subpixel, the selected subpixel lookup table including the pixel coefficients;
element-wise multiplying the intensity values of the pixels in the image by the pixel coefficients and summing products of the element-wise multiplications to generate the output, the pixel coefficients acting as weights and the output being a weighted sum of the intensity values;
7. The computer-implemented method of claim 6, further comprising: base calling the target cluster using the output, the base calling comprising: generating the output for each imaging channel in a plurality of imaging channels; and base calling the target cluster using the output for each imaging channel. 前記要素ごとの乗算は、所与の等化器係数セットのバイアスを加算し、前記バイアスは、背景ノイズ強度を平均化するＤＣオフセットである、請求項７に記載のコンピュータ実装方法。 8. The computer-implemented method of claim 7 , wherein the element-wise multiplication adds a bias for a given set of equalizer coefficients, the bias being a DC offset that averages background noise intensity. サブピクセルルックテーブルの前記バンクから、前記特定のサブピクセルに連続して隣接するサブピクセルに対応する追加のサブピクセルルックアップテーブルを選択することと、
選択された前記サブピクセルルックアップテーブル及び選択された前記追加のサブピクセルルックアップテーブルのピクセル係数に基づいて、前記信号対ノイズ比を増加させるように構成されている補間ピクセル係数を生成することと、
前記補間ピクセル係数を前記画像内の前記ピクセルの前記強度値を用いて畳み込み、出力を生成することと、
前記ターゲットクラスターを前記出力に基づいてベースコールすることと、を更に含む、請求項７に記載のコンピュータ実装方法。 selecting an additional subpixel lookup table from said bank of subpixel lookup tables corresponding to subpixels adjacent to said particular subpixel;
generating interpolated pixel coefficients based on pixel coefficients of the selected sub-pixel lookup table and the selected additional sub-pixel lookup table, the interpolated pixel coefficients being configured to increase the signal-to-noise ratio;
convolving the interpolated pixel coefficients with the intensity values of the pixels in the image to generate an output;
8. The computer-implemented method of claim 7 , further comprising base calling the target clusters based on the output. 前記画像中の前記ピクセルの前記強度値に対して、前記補間ピクセル係数を要素ごとに乗算し、前記乗算の積を合計して前記出力を生成することであって、前記補間ピクセル係数は、重みとして機能し、前記出力は、前記強度値の重み付き和である、生成すること、を更に含む、請求項７に記載のコンピュータ実装方法。 8. The computer-implemented method of claim 7, further comprising: element-wise multiplying the intensity values of the pixels in the image by the interpolated pixel coefficients and summing products of the multiplications to generate the output, wherein the interpolated pixel coefficients act as weights and the output is a weighted sum of the intensity values. 最小二乗推定、最小二乗法、最小平均二乗、及び再帰的最小二乗のうちの少なくとも１つを使用して等化器を訓練し、前記ピクセル係数を生成することを更に含む、請求項1に記載のコンピュータ実装方法。2. The computer-implemented method of claim 1, further comprising training an equalizer to generate the pixel coefficients using at least one of least squares estimation, least squares, least mean squares, and recursive least squares. サブピクセルルックアップテーブルの前記ピクセル係数が、以前に実行された配列決定ランからの訓練データのバッチで訓練された後に固定されるオフラインモードで、前記等化器を訓練することを更に含む、請求項１１に記載のコンピュータ実装方法。12. The computer-implemented method of claim 11, further comprising training the equalizer in an offline mode in which the pixel coefficients of a sub-pixel lookup table are fixed after being trained on a batch of training data from a previously performed sequencing run. サブピクセルルックアップテーブルの前記ピクセル係数が、進行中の配列決定ラン中に反復的に更新されるオンラインモードで、前記等化器を訓練することを更に含む、請求項１２に記載のコンピュータ実装方法。13. The computer-implemented method of claim 12, further comprising training the equalizer in an online mode in which the pixel coefficients of a sub-pixel lookup table are iteratively updated during an ongoing sequencing run. 前記訓練データ内の画像の以前のベースコール中に生成された４つの塩基Ａ、Ｃ、Ｇ、及びＴの各々の塩基ごとの強度分布にアクセスすることと、前記塩基ごとの強度分布のそれぞれの中心を、対応する色チャネルの塩基ごとのグラウンドトゥルースターゲット強度として選択することと、前記塩基ごとのグラウンドトゥルースターゲット強度を使用して前記等化器を訓練することと、を更に含む、請求項１３に記載のコンピュータ実装方法。 14. The computer-implemented method of claim 13, further comprising: accessing a per-base intensity distribution for each of four bases A, C, G, and T generated during previous base calling of images in the training data; selecting a center of each of the per-base intensity distributions as a per-base ground truth target intensity for a corresponding color channel; and training the equalizer using the per - base ground truth target intensities. 前記オフラインモードで前記等化器を事前訓練することと、前記オンラインモードで前記等化器を再訓練することと、を更に含む、請求項１４に記載のコンピュータ実装方法。 The computer-implemented method of claim 14 , further comprising pre-training the equalizer in the offline mode and re-training the equalizer in the online mode. 単一の等化器係数セットと予め計算された補間フィルタセットとを共に適用することにより、サブピクセルルックアップテーブルの前記バンク内に前記ルックアップテーブルを生成することを更に含み、ピクセル強度を補間して前記等化器に対する入力を生成することを含む、請求項１１に記載のコンピュータ実装方法。 12. The computer-implemented method of claim 11, further comprising generating the lookup tables in the bank of sub-pixel lookup tables by applying a single set of equalizer coefficients together with a set of pre - calculated interpolation filters, and interpolating pixel intensities to generate inputs to the equalizer. テンプレート画像に対して前記画像を位置合わせし、アフィン変換パラメータ及び非線形変換パラメータを決定することと、
前記アフィン変換パラメータ及び非線形変換パラメータを使用して、前記ターゲットクラスター及び前記追加の隣接クラスターの位置座標を前記画像の画像座標に変換し、変換されたピクセルを有する変換画像を生成することと、
前記ターゲットクラスター及び前記追加の隣接クラスターの変換された前記位置座標を使用して補間を適用し、それぞれのクラスター中心を、前記クラスター中心を含むそれぞれの変換されたピクセルの中心と同心にすることと、によって、前記ターゲットクラスターの中心を中心ピクセルの中心と同心にすることを更に含む、請求項１に記載のコンピュータ実装方法。 registering the image with respect to a template image and determining affine and non-linear transformation parameters;
transforming position coordinates of the target cluster and the additional neighboring clusters into image coordinates of the image using the affine transformation parameters and the nonlinear transformation parameters to generate a transformed image having transformed pixels;
2. The computer-implemented method of claim 1, further comprising: applying interpolation using the transformed position coordinates of the target cluster and the additional neighboring clusters to make each cluster center concentric with a center of a central pixel by: ベースコールを実施するためのコンピュータプログラム命令を記憶している非一時的コンピュータ可読記憶媒体であって、前記コンピュータプログラム命令は、プロセッサ上で実行されると、
画像にアクセスすることであって、前記画像のピクセルは、ターゲットクラスターからの強度放射及び追加の隣接クラスターからの強度放射を示す、アクセスすることと、
信号対ノイズ比を増加させるように構成されているピクセル係数を含むルックアップテーブルをルックアップテーブルのバンクから選択することと、
前記ピクセル係数を前記画像中の前記ピクセルの強度値に適用し、出力を生成することと、
前記ターゲットクラスターを前記出力に基づいてベースコールすることと、を含む方法を実装する、非一時的コンピュータ可読記憶媒体。 1. A non-transitory computer readable storage medium storing computer program instructions for performing base calling, the computer program instructions, when executed on a processor, performing:
accessing an image, the pixels of the image indicating intensity radiation from a target cluster and intensity radiation from additional adjacent clusters;
selecting a lookup table from a bank of lookup tables that includes pixel coefficients configured to increase a signal to noise ratio;
applying the pixel coefficients to intensity values of the pixels in the image to generate an output;
and base calling the target clusters based on the output . 前記ピクセル係数が、畳み込み演算を使用して前記強度値に適用される、請求項１８に記載の非一時的コンピュータ可読記憶媒体。20. The non-transitory computer-readable storage medium of claim 18, wherein the pixel coefficients are applied to the intensity values using a convolution operation. 前記ピクセル係数が、補間演算を使用して前記強度値に適用される、請求項１８に記載の非一時的コンピュータ可読記憶媒体。20. The non-transitory computer-readable storage medium of claim 18, wherein the pixel coefficients are applied to the intensity values using an interpolation operation. メモリに結合された１つ以上のプロセッサを含むシステムであって、1. A system including one or more processors coupled to a memory,
前記メモリは、ベースコールを実施するためのコンピュータ命令がロードされ、the memory is loaded with computer instructions for performing base calling;
前記コンピュータ命令は、前記１つ以上のプロセッサ上で実行されると、The computer instructions, when executed on the one or more processors,
画像にアクセスすることであって、前記画像のピクセルは、ターゲットクラスターからの強度放射及び追加の隣接クラスターからの強度放射を示す、アクセスすることと、accessing an image, the pixels of the image indicating intensity radiation from a target cluster and intensity radiation from additional adjacent clusters;
信号対ノイズ比を増加させるように構成されているピクセル係数を含むルックアップテーブルをルックアップテーブルのバンクから選択することと、selecting a lookup table from a bank of lookup tables that includes pixel coefficients configured to increase a signal to noise ratio;
前記ピクセル係数を前記画像中の前記ピクセルの強度値に適用し、出力を生成することと、applying the pixel coefficients to intensity values of the pixels in the image to generate an output;
前記ターゲットクラスターを前記出力に基づいてベースコールすることと、base calling the target clusters based on the output; and
を含むアクションを実装する、システム。Implementing actions including,system. 前記ピクセル係数が、畳み込み演算を使用して前記強度値に適用される、請求項２１に記載のシステム。The system of claim 21 , wherein the pixel coefficients are applied to the intensity values using a convolution operation. 前記ピクセル係数が、補間演算を使用して前記強度値に適用される、請求項２１に記載のシステム。The system of claim 21 , wherein the pixel coefficients are applied to the intensity values using an interpolation operation. メモリに結合された１つ以上のプロセッサを含むシステムであって、前記メモリは、ベースコールを実施するためのコンピュータ命令がロードされ、前記コンピュータ命令は、前記１つ以上のプロセッサ上で実行されると、
画像にアクセスすることであって、前記画像のピクセルは、ターゲットクラスターからの強度放射及び追加の隣接クラスターからの強度放射を示す、アクセスすることと、
信号対ノイズ比を増加させるように構成されているピクセル係数を含むルックアップテーブルをルックアップテーブルのバンクから選択することと、
前記ピクセル係数を前記画像中の前記ピクセルの強度値を用いて畳み込み、畳み込まれた特徴を生成することと、
前記畳み込まれた特徴を補間し、出力を生成することと、
前記ターゲットクラスターを前記出力に基づいてベースコールすることと、
を含むアクションを実装する、システム。 1. A system including one or more processors coupled to a memory, the memory being loaded with computer instructions for performing base calling, the computer instructions, when executed on the one or more processors, comprising:
accessing an image, the pixels of the image indicating intensity radiation from a target cluster and intensity radiation from additional adjacent clusters;
selecting a lookup table from a bank of lookup tables that includes pixel coefficients configured to increase a signal to noise ratio;
convolving the pixel coefficients with intensity values of the pixels in the image to generate convolved features ;
Interpolating the convolved features to generate an output; and
base calling the target clusters based on the output; and
Implementing actions, including , system. 前記信号対ノイズ比において増加する信号は、前記ターゲットクラスターからの前記強度放射であり、前記信号対ノイズ比において減少するノイズは、前記追加の隣接クラスターからの前記強度放射に追加のノイズ源を加えたものである、請求項２４に記載のシステム。25. The system of claim 24, wherein the signal that increases in the signal-to-noise ratio is the intensity radiation from the target cluster and the noise that decreases in the signal-to-noise ratio is the intensity radiation from the additional adjacent clusters plus additional noise sources. 選択された前記ルックアップテーブルが、サブピクセルルックアップテーブであり、ルックアップテーブルの前記バンクが、複数のサブピクセルルックアップテーブルである、請求項２４に記載のシステム。25. The system of claim 24, wherein the selected lookup table is a sub-pixel lookup table, and the bank of lookup tables is a plurality of sub-pixel lookup tables.
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