November 2018
Intermediate to advanced
272 pages
6h 51m
Japanese
book
エレガントなSciPy ―Pythonによる科学技術計算
by Juan Nunez-Iglesias, Stéfan van der Walt, Harriet Dashnow, 山崎 邦子, 山崎 康宏
Content preview from エレガントなSciPy ―Pythonによる科学技術計算
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2
1 章 エレガントな NumPy：科学 Python の基礎
----------
配列、形状は
(N_genes, N_sampled) RNA
シーケンリング
counts: array, shape (N_genes, N_samples)
（もしくは同様の手法）
RNAseq (or similar) count data where columns are individual samples
によるリード数データ列
and rows are genes.
は各標本、行は各遺伝子
lengths: array, shape (N_genes,)
配列、形状は
(N_genes,)
Gene lengths in base pairs in the same order
遺伝子長（単位は塩基対）。
counts
の行と同順
as the rows in counts.
Returns
戻り値
-------
normed : array, shape (N_genes, N_samples)
配列、形状は
(N_genes, N_sampled)
The RPKM normalized counts matrix.
RPKM
正規化されたリード数の配列
"""
最初にリード数を浮動小数点数に変換して、
RPKM
の式で
1e9
を掛ける際のオーバーフローを防ぐ
# First, convert counts to float to avoid overflow when multiplying ...
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