{job_name}_mem_gb: {num_GBs} {job_name}_time_hr: {num_hours} Specify the path to the folder containing the ESPRESSO source code as follows: espresso_path: /path/to/ESPRESSO/src If starting with raw nanopore data, specify the path to thebinfolder containing Guppy as follows: ...
If num_seeds > 1, the arg will instead be called seeds and will contain a sequence of seeds. In our "wmt_19_ende" task, we also use the predefined preprocessors seqio.preprocessors.tokenize and seqio.preprocessors.append_eos. The former uses each Feature.vocabulary to tokenize it, and th...
The calculating formula is: ( )( )∑m=1 p=1− M i ( )i=0 N−M n−i N n In which N is the total number of genes with GO annotation, n is the number of DEGs in N, M is the total num- ber of genes annotated with the particular GO term, and m is the number of ...
Kunnumakkara Journal of Biomedical Science (2024) Molecular insights into regulatory RNAs in the cellular machinery Sumin Yang Sung-Hyun Kim Jae-Yeol Joo Experimental & Molecular Medicine (2024) From computational models of the splicing code to regulatory mechanisms and therapeutic implications ...
Specifically, we sequentially applied the “preprocess_cds” (num_dim = 100, norm_method = “log,” method = “PCA,” scaling = TRUE), “reduce_dimension” (max_components = 2, umap.metric = “cosine”, umap.fast_sgd = FALSE, preprocess_method = ...
seq_inputs_length) # attention_mechanism = tf.contrib.seq2seq.LuongAttention(num_units=config.hidden_dim, memory=encoder_outputs, memory_sequence_length=self.seq_inputs_length) decoder_cell = tf.contrib.seq2seq.AttentionWrapper(decoder_cell, attention_mechanism) decoder_initial_state = decoder_...
Table 2. Control (CK) and dimethomorph-treated (HJ) (three biological replicates) raw read filters SampleBefore filter reads numAfter filter reads num (%)Reads lenGCAdapter (%)Low quality (%) CK-1 36006124 34 822 028 (96.71%) 150 56.98% 33 972 (0.09%) 1 150 082 (3.19%) CK-2 275...
self.rnn = nn.GRU(embed_size, num_hiddens,num_layers, dropout=dropout) def forward(self, X) -> Tensor: ''' Args: X: 形状 (batch_size, num_steps) Returns: ''' X = self.embedding(X) # X 的形状 (batch_size, num_steps, embed_size) ...
FL , Full-length reads, 全长转录本。从raw data 到 ROI , 在从ROI 去除 artifacts reads 之后,我们就得到了用于后续分析的clean reads。clean reads 就已经是转录本的序列了,我们首先看一下clean reads 当中,哪些是全长转录本;哪些不是全长转录本。
不同样品的测序量会有差异,最简单的标准化方式是计算counts per million (CPM),即原始reads count除以总reads数乘以1,000,000。 这种计算方式的缺点是容易受到极高表达且在不同样品中存在差异表达的基因的影响;这些基因的打开或关闭会影响到细胞中总的分子数目,可能导致这些基因标准化之后就不存在表达差异了,而原本...