It is well known that $\Gamma(u) \stackrel{u \to 0}{\sim} \frac{1}{u}$.
I am looking for more precise information on the behavior of $\Gamma(x)$ when $x$ is small, ie: $x\to 0$.
My question is then, are there accurate (for small value) inequalities for the Gamma function ?
Any other information on the behavior is also very welcome.

Using Taylor series around $u=0$, you should get $$\Gamma(u)=\frac{1}{u}-\gamma +\frac{6 \gamma ^2+\pi ^2}{12} u+O\left(u^2\right)\tag 1$$
For $u=\frac 1 {10}$, this very limited expression would give $\approx 9.52169$ while the "exact" value would be $\approx 9.51351$.
The error is lower than $0.1$% for any $0\lt x\leq \frac 1 {10}$.
Edit
It is possible to slightly improve the above approximation builging the simplest Pade approximant of $u\, \Gamma(u)$ around $u=0$. This would lead to $$\Gamma(u)=\frac 1 u \times\frac{12\gamma+(\pi^2-6\gamma^2)u}{12\gamma+(\pi^2+6\gamma^2)u}\tag 2$$ Using $(1)$ leads to overestimates while using $(2)$ leads to underestimates which makes the average much better. So, a better approximation could be $$\Gamma(u)=\frac 1 {2u}\left(1-\gamma u+\frac{1}{12} \left(6 \gamma ^2+\pi ^2\right) u^2+\frac{12\gamma+(\pi^2-6\gamma^2)u}{12\gamma+(\pi^2+6\gamma^2)u} \right)\tag 3$$ for which the error is lower than $0.01$% for any $0\lt x\leq \frac 1 {10}$.
We could also consider $$\Gamma(u)=\alpha\left(\frac{1}{u}-\gamma +\frac{6 \gamma ^2+\pi ^2}{12} u \right)+(1-\alpha)\left(\frac 1 u \times\frac{12\gamma+(\pi^2-6\gamma^2)u}{12\gamma+(\pi^2+6\gamma^2)u}\right)$$ and optimize the $\alpha$ parameter. For the consider range $\alpha\approx 0.44$ seems to be quite good leading to a maximum error lower than $0.0002$% over that range.
If we consider $0< x \leq 1$, $\alpha\approx 0.35$ leads to errors smaller than $0.6$% for the entire range.
We could also show that the Padé approximant of $u\,\Gamma(u)$ lead to relative errors lower than $1$% for the range $-0.625 \leq x \leq 1.168 $.